Are people smarter than quantum computers

Will another promise made by science soon become a reality? - What about the quantum computer?

Boundaries in today's sciences

A term that appears to most people as eerie-bizarre as it is exciting-futuristic is increasingly pushing its way into the sphere of public attention. It combines the apparent technological omnipotence of digital computing with the awe-inspiring abstraction of the most important physical theory of the 20th century. We are talking about the "quantum computer". There are no esoteric dreams of miraculous healing and soul cleansing ("quantum healing"), spiritual home furnishings ("quantum feng shui"), universally perfect love relationships ("quantum resonance") or other nonsense that esotericists like to call "quantum" and financial trading platforms that do not operate fraudulently, such as the one recently falsely associated with Elon Musk QuantumAITradebut a real emerging technological revolution that could shape the 21st century as significantly as the development of digital circuits, lasers and atomic energy shaped the 20th century.

Since the elements of conventional chips are now operating on an almost atomic scale, the end of the flagpole is gradually emerging for classic computers with the expiry of Moore's law in terms of computing speed, problem-solving capacity and efficiency in information processing. But a possibly completely new possibility is emerging to build computers that are far faster, even millions and billions of times more powerful than today's fastest computers, those quantum computers. With their help, problems could be solved that are far too complex for the “supercomputers” used today in physics, biology, weather research and elsewhere.

But aren't the building blocks of conventional computers already based largely on quantum mechanical principles, such as the transistor effect? In fact, the digital revolution of the 20th century would not have been possible without quantum physics. Nevertheless, the structure and functionality of conventional computers, the so-called “Von Neumann architecture”, are in principle also possible without quantum physical effects. Indeed, the first computers in the 1940s still consisted of macroscopic tubes, diodes and capacitors. Quantum physics was only required for their extreme miniaturization, which in the end made their enormous performance possible. While quantum effects often have a disruptive effect on conventional ("classic") chips, quantum computers are based in their core on the bizarre properties of quantum theory and therefore come with a fundamentally different architecture and functionality than classic computers. They are no longer used for information processing and storage Streams of many electrons like in classic computers, rather they control and manage data storage and processing separate Quantum particles and use their quantum properties directly. This enables quantum computers to potentially achieve an unimaginably higher computing speed than conventional computers and could allow them to master complexities that still make us shudder today due to their unpredictability and uncontrollability.

Six fields, the problems of which overwhelm today's computers - no matter how big - are intended to show in concrete terms the fantastic possibilities that quantum computers open up:

  1. Cryptography: Encodings common today are based on the re-factorization of the products of two very large prime numbers. Above a certain number of figures, this task can no longer be solved for a classic computer. In 1994, the computer scientist Peter Shor developed an algorithm with which a quantum computer could factor the largest products of prime numbers used today into their divisors within minutes. A quantum computer could easily crack conventional encryption methods for digital data, thereby threatening the entire global data security, which makes them interesting and threatening at the same time not only for the military.
  2. Solving complex optimization tasks: The task of finding the optimal solution from many variants is considered particularly tricky among mathematicians. Such problems arise in areas as diverse as industrial logistics, the design of microchips, or the optimization of traffic flows. Even with a small number of variants, classic computers drop out when calculating optimal solutions. Quantum computers, on the other hand, could solve larger optimization problems in a comparatively short time.
  3. Significant applications could be in the field of artificial intelligence: the “deep neural networks” used there are associated with tough combinatorial optimization problems that quantum computers could solve far faster and better than conventional computers. That could make machines many times smarter.
  4. Search in large databases: When searching through unsorted amounts of data, a classic computer has to look at each data point individually. The search time therefore increases linearly with the number of data points and thus quickly becomes too large for a classic computer with larger amounts of data. In 1996, the computer scientist Lov Grover published a quantum computer algorithm for which the number of necessary computing steps only increases with the square root of the number of data points. Instead of taking a billion data entries a thousand times as long as a million, this would only take a little more than 30 times as long with a quantum computer and the “Grove algorithm” - a breathtaking improvement in the case of very large numbers.
  5. Finding new chemical compounds: Even when simulating quantum systems, complex optimization problems arise again and again, where the aim is to find the best possible, i.e. energetically most favorable configuration of the electrons in complex molecules or groups of atoms from many alternatives. Theoretical physicists and chemists have grappled with such problems for decades, with rather limited success. The corresponding quantum equations are simply too difficult to solve for conventional computers. Quantum computers, on the other hand, could directly map the behavior of the electrons involved, since they themselves behave like a quantum system. With the better understanding of molecules and the details of their chemical reaction dynamics, it is possible, for example, to simulate complex protein structures, find new drugs or, for example, optimize the Haber-Bosch process for the production of fertilizers.
  6. Clarification of the electronic structure in crystals, which would significantly advance solid-state physics and materials research. New findings in these fields would give nanotechnology in particular a tremendous boost - for example, the behavior of possible new energy storage devices or components of molecular electronics could be calculated almost overnight, which would enable far more efficient battery technologies. Another application of the highest relevance would be the search for new high-temperature superconductors.

Some physicists even believe with a quantum computer any To be able to calculate problems in nature, from the behavior of black holes, the development of the very early universe, the collisions of high-energy elementary particles to the phenomenon of superconductivity and the modeling of 100 billion neurons and their connections (synapses ) in our brain. However, all of this has so far been of a purely theoretical nature, because a functioning universal quantum computer does not yet exist.

How exactly does a quantum computer actually work? Classical computers use the "bits" as the smallest possible information units, which either have the state 1 or 0 (that is, they can assume two values, hence the term "digital"). In them, the computing steps are processed sequentially, i.e. bit by bit, on the basis of digital information theory. Quantum computers, on the other hand, are subject to a completely different information theory and processing. The simplest system in quantum mechanics is the so-called “quantum bit”, or “qubit” for short. And these have it all: qubits can have different states, i.e. 0 and 1, simultaneously assume, as well as all values ​​in between (and even more so, since their values ​​are in the complex number plane). So they can be “half past one” and “half past twelve”, so to speak. This is due to the possibilities of quantum states to exist in so-called "superpositions". These are superimpositions of classic mutually exclusive states. This bizarre property of quantum particles was once the trigger for heated discussions among the fathers of quantum physics, which finally found its expression in the well-known thought experiment of the Schrödinger's cat found. In addition, different quantum particles are divided into so-called entangle Let states bring about. This, too, is a property that we do not know in our classical world (and about this there were no less heated discussions within the first generation of quantum physicists). It is as if the qubits are coupled together with an invisible spring. They are then all in direct contact with one another without any power wine effect between them. Every quantum bit "knows" immediately what the others are up to. Albert Einstein thought entanglement was physically impossible and mockingly called it "spooky long-distance relationship".

Entangled qubits are thus in a superposition of an infinite number of different states at the same time, which are also connected to one another by an invisible and immeasurable bond. To put it bluntly: the many-body system takes all of its possible States at the same time. Individual physical values ​​are only realized (with a respective probability) during a measurement. Before they are objectively indefinite - that too is another strange property in the quantum world. With the help of an appropriate algorithm, entangled qubits can now all be processed at the same time. And the power of the quantum computer lies in this parallel processing. Because the more qubits are entangled with one another, the more states can be processed in parallel. In contrast to conventional computers, whose computing power increases linearly with the number of computing components, the performance of a quantum computer increases exponentially with the number of qubits used. The performance of a quantum computer does not only double when 100 qubits are added to 100 qubits, but rather when only a single qubit is added to the 100 qubits. If you add 10, its performance increases a thousand times (more precisely 1024 times), with 20 new qubits the quantum computer is already a million times as fast, with 50 new qubits a million billion times. And with 100 new information carriers, when the performance of a classic computer has just doubled, the increase in the performance of a quantum computer can hardly be expressed in numbers.

It seems strange that quantum computers have not long been realized. After all, quantum theory had long been established by the time the modern computer was created. Nevertheless, decades passed before physicists took up the possibilities of quantum information processing. One of the reasons for this is obvious: for a long time, neither physicists nor computer scientists knew what to do with phenomena of superposition and entanglement. But there is also a second reason: in the 1940s, the American mathematician Claude Shannon founded classical information theory, which is based on the use of bits. His essay A Mathematical Theory of Communication (Mathematical foundations in information theory) is still considered the Bible of the information age and is one of the most influential scientific works of the 20th century. Shannon claimed that the principle of bits for each Form of information processing applies and for a long time computer scientists followed this view. In addition, according to the (extended) “Church-Turing thesis” of the American mathematician Alonzo Church and the British logician Alan Turing, it should be possible to effectively simulate any physical system on a classic computer. It was not until the 1980s that computer scientists realized that there are information concepts and physical simulations that go beyond digital bits and that cannot simply be handled on traditional computers, but can only be efficiently calculated on the basis of qubits. But this requires a completely new theoretical foundation, one that is explicitly about superposition and entanglement of quantum states. Such a new information theory and algorithm was not created until the late 1990s through the joint efforts of physicists and information theorists.

There are still enormous problems to be solved in the construction of quantum computers. The greatest of these is: Entangled quantum states decay very quickly under the omnipresent influence of heat and radiation - often too quickly to carry out the desired operations without errors. In this context, physicists speak of “decoherence” of the quantum states. Working with qubits almost feels like writing not on a piece of paper, but on the surface of water. While paper can last for centuries, what was written on water disappears in a fraction of a second. So it depends on mastering an insane speed. In order to overcome this hurdle, quantum engineers are pursuing a twofold strategy: on the one hand, they try to extend the life of the qubits, i.e. reduce their susceptibility to errors, and on the other, they develop algorithms that correct the errors that occur. The physicists are able to curb decoherence with the help of ultra-cold refrigerators. For the treatment of errors in individual qubits caused by decoherence, they are in turn developing better and better methods (so-called quantum error correction), which can be used to increase the reliability of quantum computers.

For many years, the concepts of qubits and quantum computers were largely theoretical. But quantum engineers have made considerable progress in their endeavors to translate these into concrete applications in recent years. So today there are numerous different promising approaches to actually produce qubits and to interlock them with one another. In principle, it is always a matter of “capturing” individual quantum systems, such as atoms or electrons, with a few tricks, entangling them with one another and then manipulating them accordingly. Here are a few examples of how this can work:

  • Ions (electrically charged atoms) are held in place by means of electric and magnetic fields and swung back and forth in a controlled manner and thereby coupled with one another as qubits.
  • The spins of atoms, which are aligned by external magnetic fields as in nuclear magnetic resonance technology, are entangled with one another.
  • Qubits can also be realized with the help of so-called quantum dots. These are special places in a solid where the mobility of the electrons is severely restricted in all directions and which, according to the laws of quantum physics, can no longer emit or absorb energy continuously, but only in discrete values. They therefore behave like giant artificial atoms.
  • Electrons that are sent on an endless loop in circular superconductors, this loop being interrupted by very thin layers of insulator (so-called SQUIDs - superconducting quantum interference devices, superconducting quantum interference units), are promising candidates for qubits. This is currently a particular focus of companies such as Google, Microsoft, IBM and Intel. The researchers use the so-called Josephson effect: the Cooper electron pairs of the superconductor can tunnel through the insulating barrier. The charge carriers can be in different quantum states - they then flow both clockwise and counterclockwise at the same time. Such superpositions can be used as qubits and entangled with one another.
  • Special chemical compounds could also be suitable as qubits. One example is a complex of a vanadium ion that is surrounded by organic sulfur compounds. The shell shields the spin of the ion inside so well that its state (and thus possible entanglements) are preserved for a long time.
  • A rather new method is to encode qubits with single photons that travel along photonic waveguides made of silicon and are then entangled with the help of networks of optical components (mirrors, beamsplitters and phase shifters).
  • The so-called topological quantum computer is still a purely theoretical concept. The concept behind it originally comes from mathematics, and it is not yet entirely clear whether and how it can be physically implemented. It is based on so-called anyons (not to be confused with the anions from aqueous solutions). These are states with particle properties in two-dimensional space and are therefore also referred to as “quasi-particles”. Anyons occur, for example, at the interfaces of insulators. Such topological qubits should form relatively stable networks and would be much better protected against interference than with other concepts.
  • But there is another concept of a quantum computer: The so-called “adiabatic quantum calculation” (also referred to as “quantum annealing”) relies on the adiabatic behavior of quantum systems to make calculations (“adiabatic” means in physics that a entire system changes without energetically exchanging with its environment). A simple quantum system is set to its basic state (state of lowest energy) and then slowly and continuously transformed into a more complicated quantum system, whose basic state represents the solution to the problem in question. The Adiabatic theorem in theoretical physics says that if this transformation is slow enough, the evolving system will remain in its ground state throughout the process. The company already had a computer based on this principle in 2007 D-Wave Systems However, its results are still controversial today.

In the meantime there are still a dozen other physical attempts at realization to generate entangled qubits that can then operate as computers. Most of them are still in their infancy despite rapid advances in this area. So far, the efforts of quantum physicists have not produced reliably functional (and universal) quantum computers. However, companies such as IBM, Google, Microsoft and Intel recently announced that they have built quantum processors or will soon be building such that consist of 50 or more qubits. At this size, they could - at least for some very special computing problems - surpass the computing capacity of any modern (classic) supercomputer. Google calls this "Quantum Supremacy" and announced in October 2019 that its engineers had succeeded in constructing a quantum computer that could for the first time solve a problem (albeit a very exotic one) that every conventional one is dealing with Computer grit its teeth. Specifically, her computer chip had Sycamore for this special arithmetic task, for which the world's best supercomputer would need 10,000 years, only needed 200 seconds. However, Google's competitor IBM doubts these results and claims that Google's bill contains an error.

Since then, not much has been heard from the big US tech firms about possible advances in quantum processor construction. Is this perhaps the calm before the storm? At the end of 2018, the US Congress signed the National Quantum Initiative Act, who is expected to invest more than $ 1.2 billion in quantum computing technology over the next 10 years. China is investing even more heavily in this field: Xi Jinping's government is providing $ 10 billion for this National Laboratory for Quantum Information Sciences available in Hefei. Chinese researchers have meanwhile also announced advances in the construction of quantum computers. The team around the multiple award-winning researcher Jian-Wei Pan from the National Laboratory for Quantum Information Sciences at the University of Science and Technology of China in Hefei reported in December 2020 that their quantum computer named Jiŭzhāng 10 billion times faster than Google's, at least when calculating a very specific problem, so-called "Gaussian boson sampling" (for which the quantum computer was built exclusively). The qubits in Jiŭzhāng are realized as photons.

Quantum computers are not yet universal calculating machines that can send e-mails, save or process files or carry out all kinds of calculations very quickly, but so-called “special purpose computers”, which up to now have only been able to solve a single, very exotic problem to demonstrate the general potential of the quantum computer. Jian-Wei Pan, however, compares the speed between quantum computers and traditional computers with the difference between "nuclear weapons and machine guns or artillery shells".

Born in 1969, I studied physics and philosophy at the University of Bonn and the École Polytechnique in Paris in the 1990s, before doing my doctorate in theoretical physics at the Max Planck Institute for the Physics of Complex Systems in Dresden, where I also did my post- Doc studies did further research in the field of nonlinear dynamics. Before that, I had also worked in the field of quantum field theories and particle physics. Meanwhile, I've been living in Switzerland for almost 20 years. For many years I have dealt with border issues in modern (as well as historical) sciences. In my books, blogs, and articles, I focus on the subjects of science, philosophy, and spirituality, especially the history of science, its relationship to spiritual traditions, and its impact on modern society. In the past I have also written on investment topics (alternative investments). My two books “Naturwissenschaft: Eine Biographie” and “Wissenschaft und Spiritualität” were published by Springer Spektrum Verlag in 2015 and 2016. I have been running my blog since 2014 at www.larsjaeger.ch.

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