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Quantum Computing

How Quantum Mechanics will Change the Tech Industry




Richard Feynman once said, “If you think you understand quantum mechanics, then you don’t understand quantum mechanics.”  While that may be true, it certainly doesn’t mean we can’t try. After all, where would we be without our innate curiosity?

To understand the power of the unknown, we’re going to untangle the key concepts behind quantum physics — two of them, to be exact (phew!). It’s all rather abstract, really, but that’s good news for us, because you don’t need to be a Nobel-winning theoretical physicist to understand what’s going on. And what’s going on? Well, let’s find out.

Laying the groundwork

We’ll start with a brief thought experiment. Austrian physicist Erwin Schrödinger wants you to imagine a cat in a sealed box. So far, so good. Now imagine a vial containing a deadly substance is placed inside the box. What happened to the cat? We cannot know to a certainty. Thus, until the situation is observed, i.e. we open the box, the cat is both dead and alive, or in more scientific terms, it is in a superposition of states. This famous thought experiment is known as the Schrödinger’s cat paradox, and it perfectly explains one of the two main phenomena of quantum mechanics.

Superposition dictates that, much like our beloved cat, a particle exists in all possible states up until the moment it is measured. “Observing” the particle immediately destroys its quantum properties, and voilà, it is once again governed by the rules of classical mechanics.

Now, things are about to get more tricky, but don’t be deterred — even Einstein was thrown-back by the idea. Described by the man himself as “spooky action at a distance”, entanglement is a connection between a pair of particles — a physical interaction that results in their shared state (or lack thereof, if we go by superposition).

Entanglement dictates that a change in the state of one entangled particle triggers an immediate, predictable response from the remaining particle. To put things into perspective, let’s throw two entangled coins into the air. Subsequently, let’s observe the result. Did the first coin land on heads? Then the measurement of the remaining coin must be tales. In other words, when observed, entangled particles counter each other’s measurements. No need to be afraid, though — entanglement is not that common. Not yet, that is.

The likely hero

“What’s the point of all this knowledge if I can’t use it?”, you may be asking. Whatever your question, chances are a quantum computer has the answer. In a digital computer, the system requires bits to increase its processing power. Thus, in order to double the processing power, you would simply double the amount of bits — this is not at all similar in quantum computers.

A quantum computer uses qubits, the basic unit of quantum information, to provide processing capabilities unmatched even by the world’s most powerful supercomputers. How? Superposed qubits can simultaneously tackle a number of potential outcomes (or states, to be more consistent with our previous segments). In comparison, a digital computer can only crunch through one calculation at a time. Furthermore, through entanglement, we are able to exponentially amplify the power of a quantum computer, particularly when comparing this to the efficiency of traditional bits in a digital machine. To visualise the scale, consider the sheer amount of processing power each qubit provides, and now double it.

Nothing’s perfect

But there’s a catch — even the slightest vibrations and temperature changes, referred to by scientists as “noise”, can cause quantum properties to decay and eventually, disappear altogether. While you can’t observe this in real time, what you will experience is a computational error. The decay of quantum properties is known as decoherence, and it is one of the biggest setbacks when it comes to technology relying on quantum mechanics.

In an ideal scenario, a quantum processor is completely isolated from its surroundings. To do so, scientists use specialised fridges, known as cryogenic refrigerators. These cryogenic refrigerators are colder than interstellar space, and they enable our quantum processor to conduct electricity with virtually no resistance. This is known as a superconducting state, and it makes quantum computers extremely efficient. As a result, our quantum processor requires a fraction of the energy a digital processor would use, generating exponentially more power and substantially less heat in the process. In an ideal scenario, that is.

A (new) world of possibilities

Weather forecasting, financial and molecular modelling, particle physics… the application possibilities for quantum computation are both enormous and prosperous.

Still, one of the most tantalising prospects is perhaps that of quantum artificial intelligence. This is because quantum systems excel at calculating probabilities for many possible choices — their ability to provide continuous feedback to intelligent software is unparalleled in today’s market. The estimated impact is immeasurable, spanning across fields and industries — from AI in the automotive all the way to medical research. Lockheed Martin, American aerospace giant, was quick to realise the benefits, and is already leading by example with its quantum computer, using it for autopilot software testing. Take notes.

The principles of quantum mechanics are also used to address issues in cybersecurity. RSA (Rivest-Shamir-Adleman) cryptography, one of the world’s go-to methods of data encryption, relies on the difficulty of factoring (very) large prime numbers. While this may work with traditional computers, which aren’t particularly effective at solving multi-factor problems, quantum computers will easily crack these encryptions thanks to their unique ability to calculate numerous outcomes simultaneously.

Theoretically, Quantum key distribution takes care of this with a superposition-based encryption system. Imagine you’re trying to relay sensitive information to a friend. To do so, you create an encryption key using qubits, which are then sent to the recipient over an optical cable. Had the encoded qubits been observed by a third party, both you and your friend will have been notified by an unexpected error in the operation. However, to maximise the benefits of QKD, the encryption keys would have to maintain their quantum properties at all times. Easier said than done.

Food for thought

It doesn’t stop there. The brightest minds around the globe are constantly trying to utilise entanglement as a mode of quantum communication. So far, Chinese researchers were able to successfully beam entangled pairs of photons through their Micius satellite over a record-holding 745 miles. That’s the good news. The bad news is that, out of the 6 million entangled photons beamed each second, only one pair survived the journey (thanks, decoherence). An incredible feat nonetheless, this experiment outlines the kind of infrastructure we may use in the future to secure quantum networks.

The quantum race also saw a recent breakthrough advancement from QuTech, a research centre at TU Delft in the Netherlands — their quantum system operates at a temperature over one degree warmer than absolute zero (-273 degrees Celsius).

While these achievements may seem insignificant to you and I, the truth is that, try after try, such groundbreaking research is bringing us a step closer to the tech of tomorrow. One thing remains unchanged, however, and that is the glaring reality that those who manage to successfully harness the power of quantum mechanics will have supremacy over the rest of the world. How do you think they will use it?

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Giles Kirkland, an experienced car expert, is passionate about all four-wheeled vehicles. He loves researching various aspects of the auto industry and tech, from cybersecurity in self-driving cars to science behind electric car batteries. Giles’ articles are available on his Twitter and Oponeo blog.

AI 101

What are Quantum Computers?




Quantum computers have the potential to dramatically increase the variety and accuracy of computations, opening up new applications for computers and enhancing our models of physical phenomenon. Yet while quantum computers are seeing increasing media coverage, many still aren’t sure of how quantum computers differ from regular computers. Let’s examine how quantum computers work, some of their applications, and their coming future.

What Is A Quantum Computer?

Before we can meaningfully examine how quantum computers operate, we need to first define quantum computers. The short definition of a quantum computer is this: a computer, based on quantum mechanics, that is able to carry out certain complex computations with much greater efficiency than traditional computers. That’s a quick definition of quantum computers, but we’ll want to take some time to really understand what separates quantum computers from traditional computers.

Regular computers encode information with a binary system: representing each bit of the data as either a one or zero. Series of ones and zeroes are chained together to represent complex chunks of information like text, images, and audio. Yet in these binary systems, the information can only ever be stored as ones and zeroes, meaning that there is a hard limit to how data is represented and interpreted and that as data becomes more complex it must necessarily become longer and longer strings of ones and zeroes.

The reason quantum computers are able to more efficiently store and interpret data is because they don’t use bits to represent data, rather they use “qubits”. Qubits are subatomic particles like photons and electrons. Qubits have a couple interesting properties that make them useful for new methods of computation. Qubits have two properties that computer engineers can take advantage of: superpositions and entanglement.

Quantum superpositions allow qubits to exist in not just the “one” state or the “zero” state, but along a continuum between these states, meaning more information can be held using qubits. Meanwhile, quantum entanglement refers to a phenomenon where pairs of qubits can be generated and if one qubit is altered the other qubit is altered, in a predictable fashion, as well. These quantum properties can be used to represent and structure complex data in more efficient ways.

How Quantum Computers Operate

Quantum “superpositions” get their name from the fact that they can be in more than one position at a time. While bits can be in just two positions, qubits can exist in multiple states at once.

Thanks in part to the existence of quantum superpositions, a quantum computer is capable of calculating many different potential outcomes at the same time. Once the calculations are done, the qubits are measured, which creates a final result through the collapse of the quantum state to either 0 or 1, meaning the result can then be interpreted by traditional computers.

Quantum computing researchers and engineers can alter the position the qubits are in by using microwaves or precision lasers.

Computer engineers can take advantage of quantum entanglement to dramatically improve the processing power of computers. Quantum entanglement refers to the fact that two qubits can be linked together in such a way that changing one of the qubits alters the other qubit in a reliable way. It’s not fully understood why qubits can establish such a relationship or how this phenomenon works exactly, but scientists do understand it well enough to potentially take advantage of it for quantum computers. Because of quantum entanglement, the addition of extra qubits to a quantum machine doesn’t just double the processing power of a computer it can scale the processing power exponentially.

If this has all seemed a bit too abstract, we can describe how superpositions are useful by imagining a maze. For a normal computer to attempt to solve a maze, it must try each path of the maze until it finds a successful route. However, a quantum computer could essentially explore all the different paths at once, since it isn’t tied down to any one given state.

All of this is to say that the properties of entanglement and superpositions make quantum computers useful because they can deal with uncertainty, they are capable of exploring more possible states and results. Quantum computers will help scientists and engineers better model and understand situations that are multi-faceted, with many variables.

What Are Quantum Computers Used For?

Now that we have a better intuition for how quantum computers operate, let’s explore the possible use cases for quantum computers.

We’ve already alluded to the fact that quantum computers can be used to carry out traditional computations at a much faster pace. However, quantum computer technology can be used to achieve things that may not even be possible, or are highly impractical, with traditional computers.

One of the most promising and interesting applications of quantum computers is in the field of artificial intelligence. Quantum computers have the power to improve the models created by neural networks, as well as the software that supports them. Google is currently using its quantum computers to assist in the creation of self-driving vehicles.

Quantum computers also have a role to play in the analysis of chemical interactions and reactions. Even the most advanced normal computers can only model reactions between relatively simple molecules, which they achieve by simulating the properties of the molecules in question. Quantum computers, however, allow researchers to create models that have the exact quantum properties as the molecules they are researching. Quicker, more accurate molecule modeling would aid in the creation of new therapeutic drugs and new materials for use in the creation of energy technology, such as more efficient solar panels.

Quantum computers can also be used to better predict weather. Weather is the confluence of many events and the formulas used to predict weather patterns are complicated, containing many variables. It can take an extremely long time to carry out all the calculations needed to predict the weather, during which the weather conditions themselves can evolve. Fortunately, the equations used to predict weather have a wave nature that a quantum computer can exploit. Quantum computers can help researchers build more accurate climate models, which are necessary in a world where the climate is changing.

Quantum computers and algorithms can also be used to help ensure people’s data privacy. Quantum cryptography makes use of the quantum uncertainty principle, where any attempt to measure an object ends up making changes to that object. Attempts to intercept communications would influence the resulting communication and show evidence of tampering.

Looking Ahead

Most of the uses for quantum computers will be confined to academics and businesses. It’s unlikely that consumers/the general public will get quantum smartphones, at least not anytime soon. This is because it requires specialized equipment to operate a quantum computer. Quantum computers are highly sensitive to disturbance, as even the most minute changes in the surrounding environment can cause qubits to shift position and drop out of the superposition state. This is called decoherence, and it’s one of the reasons that advances in quantum computers seem to come so slowly compared to regular computers. Quantum computers typically need to operate in conditions of extreme low temperatures, isolated from other electrical equipment.

Even with all the precautions, noise still manages to create errors in the calculations, and researchers are looking for ways to make qubits more reliable. To achieve quantum supremacy, where a quantum computer fully eclipses the power of a current supercomputer, qubits need to be linked together. A truly quantum supreme computer could require thousands of qubits, but the best quantum computers today can typically only deal with around 50 qubits. Researchers are constantly making in-roads towards creating more stable and reliable qubits. Experts in the field of quantum computers predict that powerful and reliable quantum devices may be here within a decade.

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Quantum Computing

Scientists Develop First-Ever High-Level Programming Language for Quantum Computers



Computer scientists at ETH Zurich have developed the first-ever high-level programming language that can program quantum computers just as safely and reliably as classical ones. The new breakthrough is a major step forward in quantum computing, making the task of programming quantum computers much easier than before. 

Martin Vechec is a computer science professor in ETH’s Secure, Reliable and Intelligent Systems Lab (SRI).

“Programming quantum computers is still a challenge for researchers,” Vechev says. “Which is why I’m so excited that we can now continue ETH Zurich’s tradition in the development of quantum computers and programming languages.”

“Our quantum programming language Silq allows programmers to utilize the potential of quantum computers better than with existing languages, because the code is more compact, faster, more intuitive and easier to understand for programmers.”

Silq was introduced at the programming languages conference PLDI 2020

Quantum Computers vs Classical Computers

Quantum computing is becoming increasingly important, and there is enormous potential with the technology. Quantum computers are capable of solving problems faster than classical computers by using entangled quantum states. It is in these states where bits of information overlap at certain points of time, and the computers have the potential to tackle issues that classical computers are incapable of solving in a reasonable timeframe. 

In the late summer of 2019, quantum computing saw another big advancement when one was able to solve a specific problem faster than the fastest classical computer. 

Even with the recent advancements, there are still many challenges. Some “quantum algorithms” are unable to be calculated on quantum hardware due to their high-level of errors. 

The New Language: Silq

Current quantum programming languages are closely related to specific hardware, and these languages are hard to deal with and result in too many errors. This is due to the necessity for extremely detailed instructions for implementing quantum algorithms.

Silq was developed in order to overcome this challenge.

“Silq is the first quantum programming language that is not designed primarily around the construction and functionality of the hardware, but on the mindset of the programmers when they want to solve a problem — without requiring them to understand every detail of the computer architecture and implementation,” says Benjamin Bichsel, a doctoral student and the one responsible for overseeing Sliq. 

Silq is the first ever high-level programming language for quantum computers, which means it is more expressive and requires less code to describe complex tasks and algorithms. These types of languages are easier to use for programmers and can be applied to different computer architectures.

The newly developed language also tackles the issue of errors. Classical computers use the method of automatically erasing values in order to relieve memory, which is called “garbage collection.” Within quantum computers, this is a bigger problem due to quantum entanglement, which can cause the previously calculated values to interact with current ones. This can lead to interference with the correct calculation, so an advanced technique of computation has to be used.

“Silq is the first programming language that automatically identifies and erases values that are no longer needed,” explains Bichsel.

In order to do this, only programming commands that do not contain any special quantum operations are used in their uncomputation method. 

“Our team of four has made the breakthrough after two years of work thanks to the combination of different expertise in language design, quantum physics and implementation. If other research and development teams embrace our innovations, it will be a great success,” says Bichsel.


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Quantum Computing

AlphaZero Algorithm Applied to Quantum Computing 



Quantum computing has become more of a focus over the last few years. Researchers and companies throughout the world are constantly working on developing this technology, which can solve extremely complicated problems that are too advanced for classical computers. 

One such group working on a quantum computer is at Aarhus University. A research group led by Professor Jacob Sherson utilized the computer algorithm AlphaZero in order to control a quantum system.

Quantum computers utilize quantum mechanics, which is a branch of physics that focuses on the smallest building blocks of our universe. One of the fundamental rules is that a system can exist in more than one state at a time. 

These rules get translated into computer language, and a quantum computer is able to perform multiple calculations at the same time. This means that a quantum computer can perform much faster than regular computers. 

The theory of quantum computers has been established, but there has yet to be a full-scale quantum computer created. 

AlphaZero is capable of learning on its own without any interjection from humans. Because of this, the algorithm has been able to defeat both humans and complex computer programs in difficult games like Go, Shogi, and Chess. AlphaZero was able to do this by competing against itself and improving over time. 

The algorithm was able to beat the leading chess program Stockfish after playing against itself for just four hours. After that impressive performance, Danish grandmaster Peter Heine Nielsen compared AlphaZero to a superior alien species.

The research group at Aarhus University has used computer simulations to demonstrate how AlphaZero can be applied to three different control problems. These could possibly be used in a quantum computer. 

“AlphaZero employs a deep neural network in conjunction with deep lookahead in a guided tree search, which allows for predictive hidden-variable approximation of the quantum parameter landscape. To emphasize transferability, we apply and benchmark the algorithm on three classes of control problems using only a single common set of algorithmic hyperparameters,” according to the study. 

The research done by the team was published in Nature Quantum Information.

Lead Ph.D. student Mogens Dalgaard spoke about how the team was impressed with AlphaZero’s ability to quickly teach itself.

“When we analyzed the data from AlphaZero we saw that the algorithm had learned to exploit an underlying symmetry of the problem that we did not originally consider. That was an amazing experience.”

The real breakthrough came from pairing AlphaZero, which is an extremely impressive algorithm on its own, with a specialized quantum optimization algorithm. 

According to Professor Jacob Sherson, “This indicates that we are still in need of human skill and expertise, and that the goal of the future should be to understand and develop hybrid intelligence interfaces that optimally exploits the strengths of both.”

The group wants to quicken the pace of development within the field, so they released the code and made it openly available. The move generated a lot of interest.

“Within a few hours I was contacted by major tech-companies with quantum laboratories and international leading universities to establish future collaboration” Jacob Sherson said. “so it will probably not be long until these methods will find use in practical experiments across the world.”

DeepMind is a UK-based Google sister-company that is responsible for both AlphaZero and AlphaGo. These systems are now showing their importance in other areas, including quantum computing. 


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