Mediaboss Marketing

Google announced this fall to much fanfare that it had demonstrated quantum supremacy that is, it performed a specific quantum computation far faster than the best classical computers could achieve. IBM promptly critiqued the claim, saying that its own classical supercomputer could perform the computation at nearly the same speed with far greater fidelity and, therefore, the Google announcement should be taken with a large dose of skepticism.

This wasnt the first time someone cast doubt on quantum computing. Last year, Michel Dyakonov, a theoretical physicist at the University of Montpellier in France, offered a slew of technical reasons why practical quantum supercomputers will never be built in an article in IEEE Spectrum, the flagship journal of electrical and computer engineering.

So how can you make sense of what is going on?

As someone who has worked on quantum computing for many years, I believe that due to the inevitability of random errors in the hardware, useful quantum computers are unlikely to ever be built.

Whats a quantum computer?

To understand why, you need to understand how quantum computers work since theyre fundamentally different from classical computers.

A classical computer uses 0s and 1s to store data. These numbers could be voltages on different points in a circuit. But a quantum computer works on quantum bits, also known as qubits. You can picture them as waves that are associated with amplitude and phase.

Qubits have special properties: They can exist in superposition, where they are both 0 and 1 at the same time, and they may be entangled so they share physical properties even though they may be separated by large distances. Its a behavior that does not exist in the world of classical physics. The superposition vanishes when the experimenter interacts with the quantum state.

Due to superposition, a quantum computer with 100 qubits can represent 2100 solutions simultaneously. For certain problems, this exponential parallelism can be harnessed to create a tremendous speed advantage. Some code-breaking problems could be solved exponentially faster on a quantum machine, for example.

There is another, narrower approach to quantum computing called quantum annealing, where qubits are used to speed up optimization problems. D-Wave Systems, based in Canada, has built optimization systems that use qubits for this purpose, but critics also claim that these systems are no better than classical computers.

Regardless, companies and countries are investing massive amounts of money in quantum computing. China has developed a new quantum research facility worth US$10 billion, while the European Union has developed a 1 billion ($1.1 billion) quantum master plan. The United States National Quantum Initiative Act provides $1.2 billion to promote quantum information science over a five-year period.

Breaking encryption algorithms is a powerful motivating factor for many countries if they could do it successfully, it would give them an enormous intelligence advantage. But these investments are also promoting fundamental research in physics.

Many companies are pushing to build quantum computers, including Intel and Microsoft in addition to Google and IBM. These companies are trying to build hardware that replicates the circuit model of classical computers. However, current experimental systems have less than 100 qubits. To achieve useful computational performance, you probably need machines with hundreds of thousands of qubits.

Noise and error correction

The mathematics that underpin quantum algorithms is well established, but there are daunting engineering challenges that remain.

For computers to function properly, they must correct all small random errors. In a quantum computer, such errors arise from the non-ideal circuit elements and the interaction of the qubits with the environment around them. For these reasons the qubits can lose coherency in a fraction of a second and, therefore, the computation must be completed in even less time. If random errors which are inevitable in any physical system are not corrected, the computers results will be worthless.

In classical computers, small noise is corrected by taking advantage of a concept known as thresholding. It works like the rounding of numbers. Thus, in the transmission of integers where it is known that the error is less than 0.5, if what is received is 3.45, the received value can be corrected to 3.

Further errors can be corrected by introducing redundancy. Thus if 0 and 1 are transmitted as 000 and 111, then at most one bit-error during transmission can be corrected easily: A received 001 would be a interpreted as 0, and a received 101 would be interpreted as 1.

Quantum error correction codes are a generalization of the classical ones, but there are crucial differences. For one, the unknown qubits cannot be copied to incorporate redundancy as an error correction technique. Furthermore, errors present within the incoming data before the error-correction coding is introduced cannot be corrected.

Quantum cryptography

While the problem of noise is a serious challenge in the implementation of quantum computers, it isnt so in quantum cryptography, where people are dealing with single qubits, for single qubits can remain isolated from the environment for significant amount of time. Using quantum cryptography, two users can exchange the very large numbers known as keys, which secure data, without anyone able to break the key exchange system. Such key exchange could help secure communications between satellites and naval ships. But the actual encryption algorithm used after the key is exchanged remains classical, and therefore the encryption is theoretically no stronger than classical methods.

Quantum cryptography is being commercially used in a limited sense for high-value banking transactions. But because the two parties must be authenticated using classical protocols, and since a chain is only as strong as its weakest link, its not that different from existing systems. Banks are still using a classical-based authentication process, which itself could be used to exchange keys without loss of overall security.

Quantum cryptography technology must shift its focus to quantum transmission of information if its going to become significantly more secure than existing cryptography techniques.

Commercial-scale quantum computing challenges

While quantum cryptography holds some promise if the problems of quantum transmission can be solved, I doubt the same holds true for generalized quantum computing. Error-correction, which is fundamental to a multi-purpose computer, is such a significant challenge in quantum computers that I dont believe theyll ever be built at a commercial scale.

[ Youre smart and curious about the world. So are The Conversations authors and editors. You can get our highlights each weekend. ]

Subhash Kak, Regents Professor of Electrical and Computer Engineering, Oklahoma State University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Image: Reuters

Here is the original post:

Quantum Computers Are the Ultimate Paper Tiger - The National Interest Online

What if we could do chemistry inside a computer instead of in a test tube or beaker in the laboratory? What if running a new experiment was as simple as running an app and having it completed in a few seconds?

For this to really work, we would want it to happen with complete fidelity. The atoms and molecules as modeled in the computer should behave exactly like they do in the test tube. The chemical reactions that happen in the physical world would have precise computational analogs. We would need a completely accurate simulation.

If we could do this at scale, we might be able to compute the molecules we want and need.

These might be for new materials for shampoos or even alloys for cars and airplanes. Perhaps we could more efficiently discover medicines that are customized to your exact physiology. Maybe we could get a better insight into how proteins fold, thereby understanding their function, and possibly creating custom enzymes to positively change our body chemistry.

Is this plausible? We have massive supercomputers that can run all kinds of simulations. Can we model molecules in the above ways today?

This article is an excerpt from the book Dancing with Qubits written by Robert Sutor. Robert helps you understand how quantum computing works and delves into the math behind it with this quantum computing textbook.

Lets start with C8H10N4O2 1,3,7-Trimethylxanthine.

This is a very fancy name for a molecule that millions of people around the world enjoy every day: caffeine. An 8-ounce cup of coffee contains approximately 95 mg of caffeine, and this translates to roughly 2.95 10^20 molecules. Written out, this is

295, 000, 000, 000, 000, 000, 000 molecules.

A 12 ounce can of a popular cola drink has 32 mg of caffeine, the diet version has 42 mg, and energy drinks often have about 77 mg.

These numbers are large because we are counting physical objects in our universe, which we know is very big. Scientists estimate, for example, that there are between 10^49 and 10^50 atoms in our planet alone.

To put these values in context, one thousand = 10^3, one million = 10^6, one billion = 10^9, and so on. A gigabyte of storage is one billion bytes, and a terabyte is 10^12 bytes.

Getting back to the question I posed at the beginning of this section, can we model caffeine exactly on a computer? We dont have to model the huge number of caffeine molecules in a cup of coffee, but can we fully represent a single molecule at a single instant?

Caffeine is a small molecule and contains protons, neutrons, and electrons. In particular, if we just look at the energy configuration that determines the structure of the molecule and the bonds that hold it all together, the amount of information to describe this is staggering. In particular, the number of bits, the 0s and 1s, needed is approximately 10^48:

10, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000.

And this is just one molecule! Yet somehow nature manages to deal quite effectively with all this information. It handles the single caffeine molecule, to all those in your coffee, tea, or soft drink, to every other molecule that makes up you and the world around you.

How does it do this? We dont know! Of course, there are theories and these live at the intersection of physics and philosophy. However, we do not need to understand it fully to try to harness its capabilities.

We have no hope of providing enough traditional storage to hold this much information. Our dream of exact representation appears to be dashed. This is what Richard Feynman meant in his quote: Nature isnt classical.

However, 160 qubits (quantum bits) could hold 2^160 1.46 10^48 bits while the qubits were involved in a computation. To be clear, Im not saying how we would get all the data into those qubits and Im also not saying how many more we would need to do something interesting with the information. It does give us hope, however.

In the classical case, we will never fully represent the caffeine molecule. In the future, with enough very high-quality qubits in a powerful quantum computing system, we may be able to perform chemistry on a computer.

I can write a little app on a classical computer that can simulate a coin flip. This might be for my phone or laptop.

Instead of heads or tails, lets use 1 and 0. The routine, which I call R, starts with one of those values and randomly returns one or the other. That is, 50% of the time it returns 1 and 50% of the time it returns 0. We have no knowledge whatsoever of how R does what it does.

When you see R, think random. This is called a fair flip. It is not weighted to slightly prefer one result over the other. Whether we can produce a truly random result on a classical computer is another question. Lets assume our app is fair.

If I apply R to 1, half the time I expect 1 and another half 0. The same is true if I apply R to 0. Ill call these applications R(1) and R(0), respectively.

If I look at the result of R(1) or R(0), there is no way to tell if I started with 1 or 0. This is just like a secret coin flip where I cant tell whether I began with heads or tails just by looking at how the coin has landed. By secret coin flip, I mean that someone else has flipped it and I can see the result, but I have no knowledge of the mechanics of the flip itself or the starting state of the coin.

If R(1) and R(0) are randomly 1 and 0, what happens when I apply R twice?

I write this as R(R(1)) and R(R(0)). Its the same answer: random result with an equal split. The same thing happens no matter how many times we apply R. The result is random, and we cant reverse things to learn the initial value.

There is a catch, though. You are not allowed to look at the result of what H does if you want to reverse its effect. If you apply H to 0 or 1, peek at the result, and apply H again to that, it is the same as if you had used R. If you observe what is going on in the quantum case at the wrong time, you are right back at strictly classical behavior.

To summarize using the coin language: if you flip a quantum coin and then dont look at it, flipping it again will yield heads or tails with which you started. If you do look, you get classical randomness.

A second area where quantum is different is in how we can work with simultaneous values. Your phone or laptop uses bytes as individual units of memory or storage. Thats where we get phrases like megabyte, which means one million bytes of information.

A byte is further broken down into eight bits, which weve seen before. Each bit can be a 0 or 1. Doing the math, each byte can represent 2^8 = 256 different numbers composed of eight 0s or 1s, but it can only hold one value at a time. Eight qubits can represent all 256 values at the same time

This is through superposition, but also through entanglement, the way we can tightly tie together the behavior of two or more qubits. This is what gives us the (literally) exponential growth in the amount of working memory.

Artificial intelligence and one of its subsets, machine learning, are extremely broad collections of data-driven techniques and models. They are used to help find patterns in information, learn from the information, and automatically perform more intelligently. They also give humans help and insight that might have been difficult to get otherwise.

Here is a way to start thinking about how quantum computing might be applicable to large, complicated, computation-intensive systems of processes such as those found in AI and elsewhere. These three cases are in some sense the small, medium, and large ways quantum computing might complement classical techniques:

As I write this, quantum computers are not big data machines. This means you cannot take millions of records of information and provide them as input to a quantum calculation. Instead, quantum may be able to help where the number of inputs is modest but the computations blow up as you start examining relationships or dependencies in the data.

In the future, however, quantum computers may be able to input, output, and process much more data. Even if it is just theoretical now, it makes sense to ask if there are quantum algorithms that can be useful in AI someday.

To summarize, we explored how quantum computing works and different applications of artificial intelligence in quantum computing.

Get this quantum computing book Dancing with Qubits by Robert Sutor today where he has explored the inner workings of quantum computing. The book entails some sophisticated mathematical exposition and is therefore best suited for those with a healthy interest in mathematics, physics, engineering, and computer science.

Intel introduces cryogenic control chip, Horse Ridge for commercially viable quantum computing

Microsoft announces Azure Quantum, an open cloud ecosystem to learn and build scalable quantum solutions

Amazon re:Invent 2019 Day One: AWS launches Braket, its new quantum service and releases

See the original post:

Quantum expert Robert Sutor explains the basics of Quantum Computing - Packt Hub

More than half (54%) of cybersecurity professionals have expressed concerns that quantum computing will outpace the development of other security tech, according to a research from Neustar.

Keeping a watchful eye on developments, 74% of organizations admitted to paying close attention to the technologys evolution, with 21% already experimenting with their own quantum computing strategies.

A further 35% of experts claimed to be in the process of developing a quantum strategy, while just 16% said they were not yet thinking about it. This shift in focus comes as the vast majority (73%) of cyber security professionals expect advances in quantum computing to overcome legacy technologies, such as encryption, within the next five years.

Almost all respondents (93%) believe the next-generation computers will overwhelm existing security technology, with just 7% under the impression that true quantum supremacy will never happen.

Despite expressing concerns that other technologies will be overshadowed, 87% of CISOs, CSOs, CTOs and security directors are excited about the potential positive impact of quantum computing. The remaining 13% were more cautious and under the impression that the technology would create more harm than good.

At the moment, we rely on encryption, which is possible to crack in theory, but impossible to crack in practice, precisely because it would take so long to do so, over timescales of trillions or even quadrillions of years, said Rodney Joffe, Chairman of NISC and Security CTO at Neustar.

Without the protective shield of encryption, a quantum computer in the hands of a malicious actor could launch a cyberattack unlike anything weve ever seen.

For both todays major attacks, and also the small-scale, targeted threats that we are seeing more frequently, it is vital that IT professionals begin responding to quantum immediately.

The security community has already launched a research effort into quantum-proof cryptography, but information professionals at every organization holding sensitive data should have quantum on their radar.

Quantum computings ability to solve our great scientific and technological challenges will also be its ability to disrupt everything we know about computer security. Ultimately, IT experts of every stripe will need to work to rebuild the algorithms, strategies, and systems that form our approach to cybersecurity, added Joffe.

The report also highlighted a steep two-year increase on the International Cyber Benchmarks Index. Calculated based on changes in the cybersecurity landscape including the impact of cyberattacks and changing level of threat November 2019 saw the highest score yet at 28.2. In November 2017, the benchmark sat at just 10.1, demonstrating an 18-point increase over the last couple of years.

During September October 2019, security professionals ranked system compromise as the greatest threat to their organizations (22%), with DDoS attacks and ransomware following very closely behind (21%).

See the article here:

Will quantum computing overwhelm existing security tech in the near future? - Help Net Security

Attempting to explain quantum computing with the comparison between quantum and classical computing is like comparing the world wide web to a typewriter, theres simply next to no comparison.

Thats not to say the typewriter doesnt have its own essential and commercially unique uses. Its just not the same.

However, explaining the enormous impact quantum computing could have if successfully rolled-out and becomes globally accessible is a bit easier.

Archer Materials Limited (ASX:AXE) CEO Dr Mohammad Choucair outlined the impact quantum computing could have on the finance industry.

In an address to shareholders and academics, Dr Choucair outlined that the global financial assets market is estimated to be worth trillions, and Im sure it comes as no surprise that any capability to optimise ones investment portfolio or capitalise on market volatility would be of great value to banks, governments and everyone in the audience.

Traders currently use algorithms to understand and, to a degree, predict the value movement in these markets. An accessible and operating quantum chip would provide immeasurable improvements to these algorithms, along with the machine learning that underpins them.

Archer is a materials technology-focused company that integrates the materials pulled from the ground with the converging materials-based technologies that have the capability to impact global industries including:

It could have an enormous impact on computing and the electric vehicles industries.

The potential for global consumer and business accessibility to quantum computing is the key differentiator between Archer Materials Ltd. and some of the other players in the market.

The companys 12CQ qubit, invented by Dr Choucair, is potentially capable of storing quantum information at room temperature.

As a result of this, the 12CQ chip could be thrown onto the motherboard of the everyday laptop, or tablet if youre tech-savvy, and operate in coexistence with a classical CPU.

This doesnt mean the everyday user can now go and live out a real-world, real-time simulation of The Matrix.

But it does mean that the laptop you have in your new, European leather tote could potentially perform extremely complex calculations to protect digital financial and communication transactions.

To head the progress of the 12CQ Project, Archer hired Dr Martin Fuechsle, a quantum physicist, who is by no means new to the high-performing Australian quantum tech industry.

In fact, Dr Fuechsle invented the worlds first single-atom transistor and offers over 10 years experience in the design, fabrication and integration of quantum devices.

Archer has moved quickly over the last 12 months and landed some significant 12CQ milestones, including the first-stage assembly of the nanoscale qubit processor chip.

Along with the accurate positioning of the qubit componentry with nanoscale precision.

Both of these being key success factors to the commercial and technological readiness of the room-temperature chip.

Most recently, Archer announced the successful and scalable assembly of qubit array components of the 12CQ room-temperature qubit processor. Commenting on the success, Dr Choucair announced: This excellent achievement advances our chip technology development towards a minimum viable product and strengthens our commercial readiness by providing credibility to the claim of 12 CQ chips being potentially scalable.

To build an array of a few qubits in less than a year means we are well and truly on track in our development roadmap taking us into 2020.

The Archer team has commercial agreements in place with the University of Sydney, to access the facilities they need to build chip prototypes at the Research and Prototype Foundry within the world-class, $150 million purpose-built Sydney Nanoscience Hub facility.

Continue reading here:

How quantum computing is set to impact the finance industry - IT Brief New Zealand

A team of scientists from the University of Chicago discovered a method by which quantum states can be integrated and controlled in everyday electronics. The teams breakthrough research resulted in the experimental creation of what theyre dubbing a quantum FM radio to transmit data over long distances. This feels like an eureka moment for quantum computing.

The teams work involves silicon carbide, a naturally occurring semiconductor used to make all sorts of electronics including light emitting diodes (LEDs) and circuit boards. Its also used in rocketry due to its ability to withstand high temperatures and in the production of sand paper presumably because its coarse. What were excited about is its potential as a conduit for controlling quantum states.

Todays quantum computers under the IBM/Google/MIT paradigm are giant, unwieldy things that absolutely wont fit on your desktop. They require lasers and sub-zero temperatures to function. You need a team of physicists standing by in an expensive laboratory just to get started. But the University of Chicago teams work may change all that.

They used good old fashioned electricity, something were pretty good at controlling, to initiate and direct quantum states in silicon carbide. That means they didnt need fancy lasers, a super cold environment, or any of that mainframe-sized stuff to produce quantum results. This wasnt the result of a single experiment, but in fact involved two significant breakthroughs.

The first, the ability to control quantum states in silicon carbide, has the potential to solve quantum computings exotic materials problem. Silicon carbide is plentiful and relatively easy to work with compared to the standard-fair physicists use which includes levitated atoms, laser-ready metals, and perfectly-flawed diamonds. This is cool, and could fundamentally change the direction most quantum computing research goes in 2020 and beyond. But its the second breakthrough that might be the most exciting.

According to a press release from the University of Chicago, the teams method solves quantum computings noise problem. Per Chris Anderson, a co-author on the teams paper:

Impurities are common in all semiconductor devices, and at the quantum level, these impurities can scramble the quantum information by creating a noisy electrical environment. This is a near-universal problem for quantum technologies.

Co-author Alexandre Bourassa added:

In our experiments we need to use lasers, which unfortunately jostle the electrons around. Its like a game of musical chairs with electrons; when the light goes out everything stops, but in a different configuration. The problem is that this random configuration of electrons affects our quantum state. But we found that applying electric fields removes the electrons from the system and makes it much more stable.

The work is still early, but it has incredible implications for the field of quantum computing. With a little tweaking, it appears that this silicon carbide-based method of wrangling quantum states could lead us to the unhackable quantum communications network sooner than many experts believed. According to the team, it would work with the existing fiber optic network that already transmits 90 percent of the worlds data.

On the outside, a quantum FM radio, that essentially sends data along frequency-modulated waves, could augment or replace existing wireless communication methods and bring about an entirely new class of technology. Were thinking something like Star Treks TriCorders, a gadget that records environmental data, processes it instantly, and uses quantum AI to analyze and interpret the results.

For more information read the Chicago teams research papers here and here.

H/t: Phys.Org

Read next: Buchardt S400 Review: Remarkable speakers near endgame material

Read more here:

Double eureka: Breakthroughs could lead to quantum 'FM radio' and the end of noise - The Next Web