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Filtering the Future QUANTUM ISSUE 03 JUN 2017 COMPUTING QUANTUM COMPUTERS AND THE POTENTIAL APPLICATIONS OF THIS REVOLUTIONARY TECHNOLOGY images: Docubytes, © by James Ball © by Docubytes, images: INTRODUCTION

INTRODUCTION

FILTERING THE FUTURE IS BASED ON THE MOST EXCITING AND SIGNIFICANT MESSAGES OF THE FILTER FROM THE LAST MONTHS.

THIS FILTERING THE FUTURE IS ABOUT QUANTUM COMPUTERS AND THE POTENTIAL APPLICATIONS OF THIS REVOLUTIONARY TECHNOLOGY. FILTERING THE FUTURE / 03

WHAT IS QUANTUM COMPUTING?

Everything in the natural world can be described by , and doing so has led to the development of everyday technologies from MRI scans, nanotechnology and the transistor. There are two quantum revolutions. The first one was in (quantum) : understanding how things work at the sub-atomic level, and that yielded some strange conclusions: particles can be in two states at the same time; two or more particles that are separated at great distance can still ‘sense’ each other; the exact position of a particle is never certain until it is measured or observed but this observation or measurement changes the situation of the particle irrevocably. In the 1920s, quantum physicists did the math that underpins these conclusions, but they were made manifest in laboratory experiments only later on in the 20th century.

The practical work on quantum computing – the second quantum revolution – started in the 1980s, with the work of Paul Benioff and Yuri Manin, , and , when scientists learned how to apply the physics and to model computers that could perform ‘quantum computations’. The main idea is that a quantum computer programs atoms to represent all possible input combinations simultaneously and run an algorithm that tests all possible combinations at once, instead of serially cycling every possibility by varying input to arrive at a solution. This method will help to solve the most complicated computations that even modern-day supercomputers take decades to do.

Why? Because quantum computation is conceptually different from ‘normal computation’, or the way ‘traditional’ computers perform their operations. Three concepts - that defy our intuition - are at the center. The first is superposition. Traditional computing depends on bits that can only take on two, binary values: 0 or 1. Qubits, their quantum analogues, can be arranged in ‘states’: something like a mixture of 0, 1 or both 0 and 1 (tertiary value). To carry out a quantum computation with qubits is to act on the 0, 1 and both at the same time. WHAT IS QUANTUM COMPUTING?

The concept of entanglement unleashes the power of these indeterminate state of qubits. Binary bits in a traditional computer are isolated from another, but inside a quantum computer all qubits are interrelated or correlated, or ‘entangled’ with another. And a quantum computer can run its computations on all ‘entangled superpositions’ simultaneously. That means that to operate on one qubit is to operate on all entangled qubits, making the computational power of a quantum computer an exponential function of its qubits (computational power = 2^qubits), impossible to describe by decomposing it into its constituent parts. For example, to describe all the states of a (binary) 50-bit traditional computer requires 50 bits of digital memory; a description of a (entangled) 50-qubit quantum computer would require 2.5 quadrillion (see for example IBM’s recent handbook on numerical benchmarks for quantum computing to define the computational power of quantum computing, or ‘volume’ of quantum computers).

That brings us to the last quantum concept: its probability amplitude. Equations in traditional computing can predict the probability of a given event, for example how likely it is that the S&P will decline by 10% or the chance the Ajax wins the Europe League. But probabilities in quantum computing – which can also be negative – can interfere with each other and depend on the other elements of the probability equation that is used. So when a quantum computer searches a data set for example, it can take shortcuts to the right answer. It does so by reducing the probability of wrong answers and increasing the probability of the right answers from its own operations.

These three properties make quantum computing so different of traditional computing, because quantum computing reverses the order and concept of a computation. Traditional computing systems deliver the output (the answer) given the input (the question). Consider, for example, that we want to know all possible computations of the number ‘1000’, using only prime numbers. Because traditional computing is binary, with isolated events and fixed probabilities, it will start factoring FILTERING THE FUTURE / QUANTUM COMPUTING 05

all possible operations with prime numbers that yield the number ‘1000’. The problem for the system is the ‘problem’ itself: what we want to know, our question. But quantum computing works otherwise, because its system uses programmed atoms that already contain every possible answer, and the problem is how to ask it. In other words, the quantum system already knows or contains how many prime number operations yield the number ‘1000’, and we only need to put the right question. So the quantum system no longer considers the operation as an ‘or…or problem’ (binary) but as ‘and…and’ (entangled superpositions) as it ‘recognizes’ all the right answers immediately that are inherent to the system. The problem is not the computation of all possible combinations or all the steps in the computational linkage, but only to filter all right answers. And that saves a lot of time.

So quantum computing is both conceptually and technologically a real ‘paradigm shift’ from traditional computing. Companies are therefore rushing to make the first working quantum computer, to reach ‘’: performing certain calculations traditional computers cannot do, like some physical processes cannot be emulated by non-quantum models. Some computations are so complex or large that traditional (super)computers cannot perform these in a finite time slot or would otherwise require an almost infinite amount of energy. Quantum computing can tackle these problems. DEVELOPING QUANTUM COMPUTERS FILTERING THE FUTURE / QUANTUM COMPUTING 07

DEVELOPING QUANTUM COMPUTERS

Until now, researchers only succeeded to build five-qubit computers and more fragile 10- to 20-qubit test systems. But the head of Google’s quantum computing effort, Harmut Neven, claims his team is on target to build a 49-qubit system by as soon as a year from now. And this target of around 50 qubits isn’t an arbitrary one: it’s the threshold of quantum supremacy. In other words, today’s top supercomputer systems can more or less still do all the same computations these 5- to 20-qubit quantum computers can do, but at around 50 qubits this becomes impossible.

But quantum computing also has its own obstacles. It is for example very expensive. That’s because quantum computers can only operate in very controlled conditions, as qubits are extremely susceptible to noise, vibrations, temperature, or fluctuating electric fields. Entangled superpositions can only be reached in ‘pure’ states, that are often just above the absolute zero of -273,15°. Creating and sustaining these conditions therefore requires a lot of energy, money and time. Not to mention the costly process of engineering and hosting quantum computers, using and creating new and rare quantum materials, and working on the edge of scientific knowledge where no one has been before and no idea seems crazy or counter-intuitive enough.

That does not withhold scientists and companies to invest and experiment with quantum computing. According to MIT, all the academic and corporate quantum researchers agree that somewhere between 30 and 100 qubits - particularly qubits stable enough to perform a wide range of computations for longer durations - is where quantum computers start to have commercial value, and as soon as two to five years from now, such systems are likely to be for sale. In the long run, they expect 100,000-qubit systems or even a million-physical-qubit system could be engineered and become functional. That will put quantum computing at an unsurmountable distance to traditional computing systems and perform computations that are for now unconceivable

One place where pioneering work is done is in the Netherlands, Delft, where QuTech DEVELOPING QUANTUM COMPUTERS

is experimenting to design a quantum computer and a new kind of qubit. A team of scientists, led by Leo Kouwenhoven, believes the qubits they are creating, called Majorana’s, will be the building blocks for their stable and functioning quantum computer and quantum internet, because of their unique physical properties. Further breakthroughs in quantum computing’s development process came recently, when an international team of scientists published a plan to build a huge quantum computer. The device, proposed in the journal Science Advances, will be as large as a football field and cost upwards of $125 million. The proposed design uses magnetic fields to trap ions, which would be used as qubits and controlled via microwaves. Intriguingly, the team claims that it could be built now, arguing that components required for the system have been demonstrated in labs. In theory, it would be far more powerful than all currently available systems. But researchers would have to face up to many engineering problems, like how to string the elements together and ensure it all stays cool. “Such high-level issues are rarely considered by people in the field of quantum computing, either because they think it’s goofy to think that big, or because in their own physical system, it is nearly impossible to fathom such a high-level view” said Christopher Monroe, a physicist from University of Maryland in College Park, to Nature. And recently, scientists from the Ion Quantum Technology Group at Sussex University claimed to produce the first ever blueprint for a large- scale quantum computer. They call it “a discovery on par with the inventing of computing itself … “and the Holy Grail of science”, so that “Life will change completely. We will be able to do certain things we could never even dream of before,” according to professor Hensinger that leads the team.

That brings us at the role of the big tech companies, and they are showing willingness to invest in quantum computing. Google researchers are betting that within a few years there will be a demonstration of quantum supremacy. And in China, Alibaba has teamed up with the prestigious Chinese Academy of Science to explore quantum computing services via the cloud. And IBM recently announced that it is launching the world’s first commercial quantum-computing service, which will allow FILTERING THE FUTURE / QUANTUM COMPUTING 09

people to make use of (currently slow) quantum hardware via the internet. And Kouwenhoven’s team recently received an undisclosed funding from Microsoft, to lead a quantum computing laboratory for cloud services (after already been backed for €50 million by Intel, and even the U.S. army). Although these cloud services will not immediately offer quantum supremacy, tech companies expect that they will do so in the coming years. They hope to reinforce their centralized power by becoming an important gatekeeper to this scarce computational resource. A possible scenario is that most quantum computing happens within the cloud, while a few large quantum computers are standing at special facilities around the world. That would require enormous investments in digital infrastructure, for example in the digital bandwidth to transform quantum computations. But what are the domains where quantum computing’s disruptive power can be applied to? APPLICATIONS FILTERING THE FUTURE / QUANTUM COMPUTING 011

APPLICATIONS

Quantum computers will help in virtual simulation or experiments. Large software programs work with millions of lines of code, large ASIC chips that have billions of transistors and trillions of different states. As we now know, a traditional computer must check every single one in the simulation, but a quantum computer can do all these calculations immediately and simultaneously. It can therefore conduct much larger and more complex simulations and experiments. That helps, for example, physicists who want to model the behavior of atoms and particles at unusual conditions (for example, very high energies that can be only created in the Large Hadron Collider at CERN) without actually creating those unusual conditions. That saves operational and fixed capital investments. There is already a significant effort in using classical computers to simulate chemical interactions, but in many cases the problems become intractable for solving classically. But the computational power of quantum computers will help chemists to create new materials, by running all types of chemical reactions among atoms in a quantum process. And right now, most drugs are developed in clinics and laboratories by testing all consequences and effects in a lengthy, risky and costly process of trial and error. Computing and mapping all the possible combinations and modifications at once will save these development time and experimentation costs. The same goes for materials science, where the properties of a newly developed (or hypothetical) material can tested and virtually applied at once. In the Economist, Michael Bolle, researcher at Bosch, foresees that quantum simulations will design batteries that will supersede the current lithium- ion technology, and Paolo Bianco, who heads the quantum-technology research team at Airbus, says that quantum-simulating a new material such as a stiffer or lighter alloy for use in airplanes or satellites would be much faster and cheaper than manufacturing and then testing the material itself. “The promise of quantum technologies”, he says, “is in engineering terms a step up in performance - not of 20%, but of a couple of orders of magnitude.”

Outside the lab, quantum computing has the power to create fully virtual worlds. Games and visual experiences are currently programmed realities in which all APPLICATIONS

interaction is computed at every moment. A quantum computer, in contrast, contains the full virtual world in its system so interaction and communication between subject and system is just as matter of playing already programed codes and algorithms. It would create a new world for gaming, by mirroring game physics to the real world, generate more intelligent behavior of non-player characters (NPCs) or even create infinite gaming worlds. And quantum computing will boost AR and VR into fully immersive, hyperrealistic virtual environments.

Another use of quantum computers is crunching huge amounts of data and machine learning. In general, quantum computers are useful whenever we have to find ‘a needle in a haystack’. Many of these are optimization problems, for example in logistics and time management. An airline logistics manager must figure out how to stage his airplanes for the best service in the shortest amount of time; a supply chain manager has a continuously changing mix of production factors, inventory, production orders, and costs must be minimized while output maximized. And investors are looking for the optimum mix of projected returns, risk assessments to create the ideally diversified portfolio (there is a web site called Quantum for Quants that is devoted to this subject). Quantum computing can immediately compute the optimal solution to these problems, because it spits with enormous speeds through massive datasets, immediately combining all data points (entanglement), adjusting them a specific, system-dependent probability (amplitude) and running all possible correlations (superposition) and hypotheses at once. Furthermore, quantum computers can run much larger and sophisticated regression analyses, and by piling Big Data, really Big Big Data together and possibly discovering correlations that no other computer is able to discover. This would be devastating for the security of traditional computing and software programs – like cybersecurity or online banking – that often use digital encryptions like the example of the factorization of prime numbers. These codes will then be cracked within a fraction of time, requiring new ways of digital coding and encryption (see NSA’s warnings).

And by simulating natural processes, quantum devices are already being used in high-precision operations. These quantum devices are connected with each FILTERING THE FUTURE / QUANTUM COMPUTING 013

other, and depend for this ‘entanglement’ mostly on light sources that can spit out photons one at a time, and detectors that can just as unfailingly catch just one. That’s quite something, considering that a 60-watt bulb is putting out approximately 100,000,000,000,000,000,000 every second, a job only highly sensitive quantum sensors can perform. These quantum sensors are for example used by RSK, an environmental consultancy, for the civil engineering of smart cities and future infrastructure deployment, and quantum gravimeters could help precisely mapping geological features from their gravitational forces alone, creating a kind of ‘Google Maps for Gravity’. A good gravimeter is also a good accelerometer, which are used in portable and connected devices, like our smartphone. And a good accelerometer is also a good vibration sensor, used in natural resource exploration. Once all these high-precision devices are small and good enough, they will be of great interest to carmakers, and in particular to the autonomous-vehicle industry. Or the military, to spot ‘silent’ torpedoes or submarines. This variety of examples shows the potential of quantum devices for commercial and industrial goals.

These quantum principles apply to the human body as well. NVision, a German startup, uses nanodiamonds (which hold the potential as a solid-state alternative to trapped ions for quantum computing at room temperature) and quantum computers to make MRI techniques much more faster and cheaper (around 40 times normal speed and at a quarter of the cost). These nanodiamonds – or ‘quantum dots’ – can also be used in gene-editing techniques that operate at the nano-level, like CRISPR. And position emission tomography (PET) uses entangled photons to detect abnormalities in biologically active molecules. Spotting these abnormalities – very precise and in fraction of time – can help to detect cancer in a very early stage, discover infectious diseases or in neuroimaging (see this and this paper for a short range of applications). Ghost imaging also uses entangled photons in the beam of lasers and light, and is being explored in the U.S. army to target objects with a light beam, but can also be used in X-ray technology, holography and visual imaging and construction or even generate ‘invisible objects’. These are all applications that will help doctors, scientists, investors, managers and engineers with diagnostic, WHAT’S NEXT? FILTERING THE FUTURE / QUANTUM COMPUTING 015

WHAT’S NEXT?

Progress in quantum computing has been relatively slow, because first quantum mechanics itself and its mathematical foundations had to be discovered, followed by an understanding how to build a quantum computer and its components. But development in this field is now accelerating, and in the foreseeable future quantum computers will overtake traditional computing systems. That will help to revive Moore’s law, which is currently dying as traditional computing systems reach their physical and structural limits, but now at a much faster pace.

However, quantum technologies are often viewed as risky, because many of the approaches are technologically so far beyond the current technological state of the art and because of the inherent uncertainty in the process of quantum computing. There is an analogy with deep learning algorithms, in which it is also not completely clear how a neural network comes to a certain solution and whether there are any systemic risks involved when we are building systems that are increasingly becoming black boxes.

But as a whole line of quantum devices and approaches are now nearing market- readiness and some are already in use, the possible benefits will outweigh disadvantages and doubts. For example, D-Wave’s 2000Q, which has 2,000 qubits and quantum annealing algorithms, is a working model for practical and quick quantum computations (and still much, much faster than normal computers). NASA, for example, already uses D-Wave quantum computers for robotics missions, Google uses them for search, image labeling, and voice recognition operations. And Volkswagen uses D-Wave’s system to predict taxi traffic patterns in Beijing. All three show impressive results.

And according to Tom Polk of the White House Office for Science and Technology Policy, “we certainly expect there are many additional things that we’ll be able to do with quantum beyond the things we know of”, having no idea “of all the things we’d be able to build with the transistor, and we see the same thing with quantum.”