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Quantum Computing

Researchers Develop Method for Measuring Quantum Computers

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Researchers at the University of Waterloo have developed a method for measuring the performance of quantum computers, and it could help establish universal standards for the machines. 

The new method is called cycled benchmarking, and researchers use it to assess the potential of scalability. The method is also used to compare different quantum platforms against each other. 

Joel Wallman is an assistant professor at Waterloo’s Faculty of Mathematics and Institute for Quantum Computing.

“This finding could go a long way toward establishing standards for performance and strengthen the effort to build a large-scale, practical quantum computer,” said Wallman. “A consistent method for characterizing and correcting the errors in quantum systems provides standardization for the way a quantum processor is assessed, allowing progress in different architectures to be fairly compared.”

Cycle Benchmarking helps quantum computing users to compare competing hardware platforms and increase the capability of each platform to come up with solutions for whatever they are working on.

At this point in time, the quantum computing race is becoming apparent all around the world. The amount of cloud quantum computing platforms and offerings are rising, and major companies like Microsoft, IBM, and Google are constantly developing new technology. 

The cycle benchmarking method works by determining the total probability of error under any given quantum computing applications. This takes place when the application is implemented through randomized compiling. Cycle benchmarking provides the first cross-platform means of measuring and comparing the capabilities of quantum processors, and it is customized depending on the applications that the users are working on. 

Joseph Emerson is a faculty member at IQC.

“Thanks to Google’s recent achievement of quantum supremacy, we are now at the dawn of what I call the `quantum discovery era’, Emerson said. “This means that error-prone quantum computers will deliver solutions to interesting computational problems, but the quality of their solutions can no longer be verified by high-performance computers.

“We are excited because cycle benchmarking provides a much-needed solution for improving and validating quantum computing solutions in this new era of quantum discovery.”

Emerson and Wallman founded Quantum Benchmark Inc., an IQC spin-off. It licensed the technology to world leading companies within the quantum computing field, including Google’s Quantum AI effort.

Quantum mechanics turned quantum computers into extremely powerful machines for computing. Quantum computers are capable of solving complex problems more efficiently than traditional or digital computers. 

Quibits are the basic processing unit in a quantum computer, but they are extremely fragile. Any type of imperfection or source of noise in the system can lead to certain errors that cause incorrect solutions under a quantum computation.

The first step to going further with quantum computing is to gain control over a small-scale quantum computer with one or two quibits. A larger quantum computer could perform more complex tasks such as machine learning or complex system simulation, which could lead to advancements like the discovery of new pharmaceutical drugs. The problem is that engineering a larger quantum computer is more challenging, and the possibility of error is greater as quibits are added and the quantum system scales. 

A profile of the noise and errors are produced when a quantum system is characterized. This indicates if the processor is performing the calculations that it is being requested to do. All significant errors need to be characterized in order to understand the performance of a quantum computer or to scale up. 

Wallman, Emerson, and a group of researchers at the University of Innsbruck came up with a method to assess all error rates affecting a quantum computer. The new technique was implemented for the ion trap quantum computer at the University of Innsbruck, and it found that error rates don’t rise as the size of that quantum computers scales up. 

“Cycle benchmarking is the first method for reliably checking if you are on the right track for scaling up the overall design of your quantum computer,” said Wallman. “These results are significant because they provide a comprehensive way of characterizing errors across all quantum computing platforms.”

 

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Quantum Computing

Physicists Develop Algorithm to Make More Efficient Quantum Calculations

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Quantum computing is one of the most powerful tools available to society, with the potential to solve many of the extremely complex problems that classical computers cannot handle. However, in order to achieve the most powerful quantum computers, there needs to be an increase in efficiency.

Quantum physicists at the University of Sussex are addressing this efficiency problem. They have created a new algorithm that can increase the speed of the rate of calculations in the quantum computers currently being developed. The algorithm provides a new way to route the ions around the quantum computer, which increases the efficiency of the calculations. 

The ‘routing algorithm’ was detailed in the research paper titled “Efficient Qubit Routing for a Globally Connected Trapped Ion Quantum Computer,” which was published in the journal Advanced Quantum Technologies.

The team was led by Professor Winfried Hensinger and included Mark Webber, Dr. Steven Haerbert, and Dr. Sebastian Weidt. 

Hensinger and Webber have recently launched their own company, Universal Quantum. It aims to build the first-ever large scale quantum computer, and various high-level tech investors have expressed interest

Routing Algorithm

The routing algorithm works by regulating the traffic in a quantum computer, making it possible for quibits to be physically transported over long distances. This allows the quibits to interact with others, and the data is able to move efficiently within the quantum computer without any jams. 

One of the foundational aspects of quantum computers is quantum bits, or quibits, which are used to process information. The team first analysed a ‘trapped ion’ quantum computer, which consists of silicon microchips with charged atoms. These charged atoms, or ions, levitate above the surface of the microchip, and they are used to store data. Each ion is able to hold one quantum bit of information.

In order to do calculations on this type of quantum computer, the ions need to be moved around. The power of the quantum computer depends on how fast and efficiently this can happen.

Superconducting vs Trapped Ion

There are two main devices that are used within the field of quantum computing: superconducting devices and trapped ion devices. 

Superconducting devices are used by some of the big name companies like IBM and Google, while the trapped ion devices are used by the team at the University of Sussex and other companies. 

Superconducting quantum computers rely on stationary quibits, and most of the time these can only interact with quibits that are right next to each other. In order for calculations to take place between quibits that are not directly next to each other, there needs to be communication through a chain of adjacent quibits. 

As the information moves from one qubit to the next and so on, it becomes more corrupt the longer the chain is. Because of this, superconducting quantum computers are seen by the team as having a limited computational power. 

Due to these limitations, the team opted to develop a new routing algorithm for trapped ion architecture. The current method for measuring the computational power of near term quantum computers is ‘Quantum Volume,’ which the team was able to use to compare their model to the superconducting ones. 

The team found that their trapped-ion model was more consistent and performed better than that of the superconducting qubit, and this was due to their algorithm allowing quibits to directly interact with more quibits. This method results in a higher expected computational power. 

“We can now predict the computational power of the quantum computers we are constructing. Our study indicated a fundamental advantage for trapped ion devices, and the new routing algorithm will allow us to maximize the performance of early quantum computers,” Webber said. 

According to Hensinger, “Indeed, this work is yet another stepping stone towards building practical quantum computers that can solve real world problems.”

 

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Quantum Computing

How Quantum Mechanics will Change the Tech Industry

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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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AI 101

What are Quantum Computers?

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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.

Future of Quantum Computing

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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