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In this weeks podcast, Enrique Blair on quantum computing, Walter Bradley Center director Robert J. Marks talks with fellow computer engineer Enrique Blair about why Quantum mechanics pioneer Niels Bohr said, If quantum mechanics hasnt profoundly shocked you, you havent understood it yet. Lets look at some of the reasons he said that:

The Show Notes and transcript follow.

Enrique Blair: Its really quite different from our daily experience. Quantum mechanics really is a description of the world at the microscopic scale. And its really weird, because there are things that initially we thought maybe were particles but then we learned that they have wave-like behaviors. And there are other things that we thought were waves and then we discovered they have particle-like behaviors.

But thats hardly the strangest part. The strangest part is that a quantum particle does not actually have a position until we measure it, according to the generally accepted Copenhagen interpretation of quantum mechanics.

Robert J. Marks: Whats the Copenhagen interpretation?

Enrique Blair (pictured): Its that the quantum mechanical wave function describes measurement outcomes in probabilities. You cant predict with certainty the outcome of a measurement. Which is really shocking, because in the classical world, if you have a particle and you know its position and its velocity, you can predict where its going to be in the next second or minute or hour. Now in quantum mechanics, the really weird thing is, we say that a particle doesnt even have a position until you measure its position.

Robert J. Marks: It doesnt exist?

Enrique Blair: Not that it doesnt exist, but its position is not defined.

Dr. Marks compared quantum mechanics (QM) to one of the characters in a 1999 film, Mystery Men, featuring inept amateur superheroes, including one who says, Im invisible as long as nobodys looking at me. With QM, thats not a joke. The quantum particle doesnt have a position until we measure it. But how did we discover this? The story goes back to the early 1800s when British physicist Thomas Young (17731829) did a famous experiment with a card held up to a small window

Enrique Blair: Youngs double-slit experiment goes all the way back to 1801, where Young shot light at a couple of slits and then the light passing through the slits would show up on a screen behind them.

So light behaves like a wave, with interference patterns. But what happens when we try doing the same thing with a single particle of lighta photon? Thats something we can do nowadays.

Enrique Blair: We can reduce a beam of light so that its single photon. One photon is emitted at a time, and were shooting it at our double slit again.

What happens when each particle of light goes through these slits? Well, each particle splats up against this screen, and so you can know where the photon hits. But if you do this over a long period of time, the interference pattern shows up again. You have particles hitting the screen, so we see the particle behavior. But we also see the interference pattern which suggests that okay, weve got some wave interference going on here.

So the only way to explain both of these at the same time is that each photon, which is an indivisible packet of light, has to go through both slits at the same time and interfere with itself, and then the buildup of many, many photons gives you that interference pattern.

Robert J. Marks: A particle was hypothesized to go through both slits?

Enrique Blair: Yes, and thats the mind-blowing ramification of this thing.

Robert J. Marks: How do we decide which slit the particles go through? Suppose we went down and we tried to measure? We put out one photon and we put it through the double slit. Weve tried to measure which slit it went through. If its a particle, it can only go through one, right?

Enrique Blair: Right. That introduces this concept of measurement. Like you said, which slit does it go through? Now the interesting thing is, if we know which slit it goes through maybe we set up a detector and we say, Hey, did it go through Slit One or Slit Two? we detect that, we measure it and the interference pattern goes away because now its gone through one slit only, not both.

Robert J. Marks: Just by the act of observation, we are restricting that photon to go through one slit or the other. Observation really kind of screws things up.

Enrique Blair: Thats right. This is one of the things that is hard to understand about quantum mechanics. In the classical world that we deal with every day, we can just observe something and we dont have to interact with it. So we can measure somethings position or its velocity without altering it. But in quantum mechanics, observation or measurement inherently includes interacting with that thing, that particle.

Again, youve got this photon that goes through both slits, but then you measure it and it actually ends up going through oneonce you measure it.

Robert J. Marks: This reminds me again of Invisible Boy in Mystery Men. The photon goes through one of the two slits while youre looking at it. Unless you look away. Then it goes through both slits.

Enrique Blair: Right. Very tricky, those photons.

Next: How scientists have learned to work with the quantum world

Note: The illustration of the double-slit experiment in physics is courtesy NekoJaNekoJa and Johannes Kalliauer (CC BY-SA 4.0).

You may also enjoy: A materialist gives up on determinism. Evolutionary biologist Jerry Coyne undercuts his own argument against free will by admitting that quantum phenomena are real (Michael Egnor)

Quantum randomness gives nature free will. Whether or not quantum randomness explains how our brains work, it may help us create unbreakable encryption codes (Robert J. Marks)

Podcast Transcript Download

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Here's Why the Quantum World Is Just So Strange - Walter Bradley Center for Natural and Artificial Intelligence

By the times that A.I. comes back and tells you that, then we have reached artificial general intelligence, and you should be very scared or very excited, depending on your point of view, Dr. Tegmark said. The reason Im working on this, honestly, is because what I find most menacing is, if we build super-powerful A.I. and have no clue how it works right?

Dr. Thaler, who directs the new institute at M.I.T., said he was once a skeptic about artificial intelligence but now was an evangelist. He realized that as a physicist he could encode some of his knowledge into the machine, which would then give answers that he could interpret more easily.

That becomes a dialogue between human and machine in a way that becomes more exciting, he said, rather than just having a black box you dont understand making decisions for you.

He added, I dont particularly like calling these techniques artificial intelligence, since that language masks the fact that many A.I. techniques have rigorous underpinnings in mathematics, statistics and computer science.

Yes, he noted, the machine can find much better solutions than he can despite all of his training: But ultimately I still get to decide what concrete goals are worth accomplishing, and I can aim at ever more ambitious targets knowing that, if I can rigorously define my goals in a language the computer understands, then A.I. can deliver powerful solutions.

Recently, Dr. Thaler and his colleagues fed their neural network a trove of data from the Large Hadron Collider, which smashes together protons in search of new particles and forces. Protons, the building blocks of atomic matter, are themselves bags of smaller entities called quarks and gluons. When protons collide, these smaller particles squirt out in jets, along with whatever other exotic particles have coalesced out of the energy of the collision. To better understand this process, he and his team asked the system to distinguish between the quarks and the gluons in the collider data.

We said, Im not going to tell you anything about quantum field theory; Im not going to tell you what a quark or gluon is at a fundamental level, he said. Im just going to say, Heres a mess of data, please separate it into basically two categories. And it can do it.

See the rest here:
Can a Computer Devise a Theory of Everything? - The New York Times

Theres a lingering fear among crypto investors that their bitcoin might get swooped by a hacker.

Thats not very likely, but its not impossible either, particularly once quantum computing gets into the wrong hands. Last year Googles quantum computer called Sycamore was given a puzzle that would take even the most powerful supercomputers 10 000 years to solve and completed it in just 200 seconds, according to Nature magazine.

That kind of processing power unleashed on the bitcoin blockchain which is a heavily encrypted ledger of all bitcoin transactions is a cause for concern.

Read:

The encryption technology used by the bitcoin blockchain has proven itself robust enough to withstand any and all attacks. Thats because of its brilliant design, and ongoing improvements by an ever-growing community of open-source cryptographers and developers.

A report by research group Gartner (Hype Cycle for Blockchain Technologies, 2020) suggests blockchain researchers are already anticipating possible attacks by quantum computers that are perhaps five to 10 years away from commercial availability. Its a subject called Postquantum blockchain which is a form of blockchain technology using quantum-resistant cryptographic algorithms that can resist attack by future quantum computers.

The good news is that quantum-resistant algorithms are likely to remain several steps ahead of the hackers, but its an issue that is drawing considerable attention in the financial, security and blockchain communities.

Postquantum cryptography is not a threat just yet, but crypto exchanges are going to have to deploy quantum-resistant technologies in the next few years, before quantum computers become generally available.

Phishing is probably a bigger threat

In truth, youre far more likely to be hit by a phishing scam, where identity thieves use emails, text messages and fake websites to get you to divulge sensitive personal information such as bank account or crypto exchange passwords.

As a user, you should be using LastPass or similar software to generate complex passwords, along with two-factor authentication (requiring the input of a time-sensitive code before you can access your crypto exchange account).Most good exchanges are enabled for this level of security.

There are many sad stories of bitcoin theft, but these are usually as a result of weak security on the part of the bitcoin holder, much like leaving your wallet on the front seat of your car while you pop into the shop for a minute.

Like all tech breakthroughs, quantum computing can be used for good and bad.

On the plus side, it will vastly speed drug discovery, molecular modelling and code breaking. It will also be a gift to hackers and online thieves, which is why financial services companies are going to have to invest in defensive technologies to keep customer information and assets safe.

Most crypto exchanges invest substantial amounts in security. The vast majority of crypto assets (about 97%) are stored in encrypted, geographically-separated, offline storage. These cannot be hacked.

The risk emerges when bitcoin are moved from offline (or cold storage) to online, such as when a client is about to transact.

But even here, the level of security is usually robust. A further level of protection is the insurance of all bitcoin that are stored in online systems. They also have systems in place to prevent any employee from making off with clients assets, requiring multiple keys before a bitcoin transaction is authorised.

There have been hacks on crypto exchanges in the past (though not on the blockchain itself), and millions of dollars in crypto assets stolen. In more recent years, this has become less common as exchanges moved to beef up their security systems.

In 2014 Mt.Gox, at the time responsible for about 70% of all bitcoin transactions in the world, suffered an attack when roughly 800000 bitcoin, valued at $460 million, were stolen. In 2018, Japan-based crypto exchange Coincheck was hit with a $534 million fraud impacting 260000 investors.

As the value of bitcoin and other crypto assets increases, the incentive for hackers rises proportionately, which is why problems such as quantum-enabled thievery are already being addressed.

Read:Moneyweb Crypto glossary

FREE WEBINAR:New Cryptocurrency Regulations: What does this mean for the crypto market?

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Is the blockchain vulnerable to hacking by quantum computers? - Moneyweb.co.za

In a new realm of materials, PhD student Thanh Nguyen uses neutrons to hunt for exotic properties that could power real-world applications.

Thanh Nguyen is in the habit of breaking down barriers. Take languages, for instance: Nguyen, a third-year doctoral candidate in nuclear science and engineering (NSE), wanted to connect with other people and cultures for his work and social life, he says, so he learned Vietnamese, French, German, and Russian, and is now taking an MIT course in Mandarin. But this drive to push past obstacles really comes to the fore in his research, where Nguyen is trying to crack the secrets of a new and burgeoning branch of physics.

My dissertation focuses on neutron scattering on topological semimetals, which were only experimentally discovered in 2015, he says. They have very special properties, but because they are so novel, theres a lot thats unknown, and neutrons offer a unique perspective to probe their properties at a new level of clarity.

Topological materials dont fit neatly into conventional categories of substances found in everyday life. They were first materialized in the 1980s, but only became practical in the mid-2000s with deepened understanding of topology, which concerns itself with geometric objects whose properties remain the same even when the objects undergo extreme deformation. Researchers experimentally discovered topological materials even more recently, using the tools of quantum physics.

Within this domain, topological semimetals, which share qualities of both metals and semiconductors, are of special interest to Nguyen.They offer high levels of thermal and electric conductivity, and inherent robustness, which makes them very promising for applications in microelectronics, energy conversions, and quantum computing, he says.

Intrigued by the possibilities that might emerge from such unconventional physics, Nguyen is pursuing two related but distinct areas of research: On the one hand, Im trying to identify and then synthesize new, robust topological semimetals, and on the other, I want to detect fundamental new physics with neutrons and further design new devices.

My goal is to create programmable artificial structured topological materials, which can directly be applied as a quantum computer, says Thanh Nguyen. Credit: Gretchen Ertl

Reaching these goals over the next few years might seem a tall order. But at MIT, Nguyen has seized every opportunity to master the specialized techniques required for conducting large-scale experiments with topological materials, and getting results. Guided by his advisor,Mingda Li, the Norman C Rasmussen Assistant Professor and director of theQuantum Matter Groupwithin NSE, Nguyen was able to dive into significant research even before he set foot on campus.

The summer, before I joined the group, Mingda sent me on a trip to Argonne National Laboratory for a very fun experiment that used synchrotron X-ray scattering to characterize topological materials, recalls Nguyen. Learning the techniques got me fascinated in the field, and I started to see my future.

During his first two years of graduate school, he participated in four studies, serving as a lead author in three journal papers. In one notable project,described earlier this yearinPhysical Review Letters, Nguyen and fellow Quantum Matter Group researchers demonstrated, through experiments conducted at three national laboratories, unexpected phenomena involving the way electrons move through a topological semimetal, tantalum phosphide (TaP).

These materials inherently withstand perturbations such as heat and disorders, and can conduct electricity with a level of robustness, says Nguyen. With robust properties like this, certain materials can conductivity electricity better than best metals, and in some circumstances superconductors which is an improvement over current generation materials.

This discovery opens the door to topological quantum computing. Current quantum computing systems, where the elemental units of calculation are qubits that perform superfast calculations, require superconducting materials that only function in extremely cold conditions. Fluctuations in heat can throw one of these systems out of whack.

The properties inherent to materials such as TaP could form the basis of future qubits, says Nguyen. He envisions synthesizing TaP and other topological semimetals a process involving the delicate cultivation of these crystalline structures and then characterizing their structural and excitational properties with the help of neutron and X-ray beam technology, which probe these materials at the atomic level. This would enable him to identify and deploy the right materials for specific applications.

My goal is to create programmable artificial structured topological materials, which can directly be applied as a quantum computer, says Nguyen. With infinitely better heat management, these quantum computing systems and devices could prove to be incredibly energy efficient.

Energy efficiency and its benefits have long concerned Nguyen. A native of Montreal, Quebec, with an aptitude for math and physics and a concern for climate change, he devoted his final year of high school to environmental studies. I worked on a Montreal initiative to reduce heat islands in the city by creating more urban parks, he says. Climate change mattered to me, and I wanted to make an impact.

At McGill University, he majored in physics. I became fascinated by problems in the field, but I also felt I could eventually apply what I learned to fulfill my goals of protecting the environment, he says.

In both classes and research, Nguyen immersed himself in different domains of physics. He worked for two years in a high-energy physics lab making detectors for neutrinos, part of a much larger collaboration seeking to verify the Standard Model. In the fall of his senior year at McGill, Nguyens interest gravitated toward condensed matter studies. I really enjoyed the interplay between physics and chemistry in this area, and especially liked exploring questions in superconductivity, which seemed to have many important applications, he says. That spring, seeking to add useful skills to his research repertoire, he worked at Ontarios Chalk River Laboratories, where he learned to characterize materials using neutron spectroscopes and other tools.

These academic and practical experiences served to propel Nguyen toward his current course of graduate study. Mingda Li proposed an interesting research plan, and although I didnt know much about topological materials, I knew they had recently been discovered, and I was excited to enter the field, he says.

Nguyen has mapped out the remaining years of his doctoral program, and they will prove demanding. Topological semimetals are difficult to work with, he says. We dont yet know the optimal conditions for synthesizing them, and we need to make these crystals, which are micrometers in scale, in quantities large enough to permit testing.

With the right materials in hand, he hopes to develop a qubit structure that isnt so vulnerable to perturbations, quickly advancing the field of quantum computing so that calculations that now take years might require just minutes or seconds, he says. Vastly higher computational speeds could have enormous impacts on problems like climate, or health, or finance that have important ramifications for society. If his research on topological materials benefits the planet or improves how people live, says Nguyen, I would be totally happy.

Read more from the original source:
Cracking the Secrets of an Emerging Branch of Physics: Exotic Properties to Power Real-World Applications - SciTechDaily

Quantum computing is bright and shiny, with demonstrations by Google suggesting a kind of transcendent ability to scale beyond the heights of known problems.

But there's a real bummer in store for anyone with their head in the clouds: All that glitters is not gold, and there's a lot of hard work to be done on the way to someday computing NP-hard problems.

"ETL, if you get that wrong in this flow-based programming, if you get the data frame wrong, it's garbage in, garbage out," according to Christopher Savoie, who is the CEO and a co-founder of a three-year-old startup, Zapata Computing of Boston, Mass.

"There's this naive idea you're going to show up with this beautiful quantum computer, and just drop it in your data center, and everything is going to be solved it's not going to work that way," said Savoie, in a video interview with ZDNet. "You really have to solve these basic problems."

"There's this naive idea you're going to show up with this beautiful quantum computer, and just drop it in your data center, and everything is going to be solved it's not going to work that way," said Savoie, in a video interview with ZDNet. "You really have to solve these basic problems."

Zapata sells a programming tool for quantum computing, called Orquestra. It can let developers invent algorithms to be run on real quantum hardware, such as Honeywell's trapped-ion computer.

But most of the work of quantum today is not writing pretty algorithms, it's just making sure data is not junk.

"Ninety-five percent of the problem is data cleaning," Savoie told ZDNet. "There wasn't any great toolset out there, so that's why we created Orquestra to do this."

The company on Thursday announced it has received a Series B round of investment totaling $38 million from large investors that include Honeywell's venture capital outfit and returning Series A investors Comcast Ventures, Pitango, and Prelude Ventures, among others. The company has now raised $64.4 million.

Also:Honeywell introduces quantum computing as a service with subscription offering

Zapata was spun out of Harvard University in 2017 by scholars including Aln Aspuru-Guzik, who has done fundamental work on quantum. But a lot of what is coming up are the mundane matters of data prep and other gotchas that can be a nightmare in a bold new world of only partially-understood hardware.

Things such as extract, transform, load, or ETL, which become maddening when prepping a quantum workload.

"We had a customer who thought they had a compute problem because they had a job that was taking a long time; it turned out, when we dug in, just parallelizing the workflow, the ETL, gave them a compute advantage," recalled Savoie.

Such pitfalls, said Savoie, are thingsthat companies don't know are an issue until they get ready to spend valuable time on a quantum computer and code doesn't run as expected.

"That's why we think it's critical for companies to start now," he said, even though today's noisy intermediate-scale quantum, or NISQ, machines have only a handful of qubits.

"You have to solve all these basic problems we really haven't even solved yet in classical computing," said Savoie.

The present moment in time in the young field of quantum sounds a bit like the early days of microcomputer-based relational databases. And, in fact, Savoie likes to make an analogy to the era of the 1980s and 1990s, when Oracle database was taking over workloads from IBM's DB/2.

Also:What the Google vs. IBM debate over quantum supremacy means

"Oracle is a really good analogy, he said. "Recall when SQL wasn't even a thing, and databases had to be turned on a per-on-premises, as-a-solution basis; how do I use a database versus storage, and there weren't a lot of tools for those things, and every installment was an engagement, really," recalled Savoie.

"There are a lot of close analogies to that" with today's quantum, said Savoie. "It's enterprise, it's tough problems, it's a lot of big data, it's a lot of big compute problems, and we are the software company sitting in the middle of all that with a lot of tools that aren't there yet."

Mind you, Savoie is a big believer in quantum's potential, despite pointing out all the challenges. He has seen how technologies can get stymied, but also how they ultimately triumph. He helped found startup Dejima, one of the companies that became a component of Apple's Siri voice assistant, in 1998. Dejima didn't produce an AI wave, it sold out to database giant Sybase.

"We invented this natural language understanding engine, but we didn't have the great SpeechWorks engine, we didn't have 3G, never mind 4G cell phones or OLED displays," he recalled. "It took ten years from 1998 till it was a product, till it was Siri, so I've seen this movie before I've been in that movie."

But the technology of NLP did survive and is now thriving. Similarly, the basic science of quantum, as with the basic science of NLP, is real, is validated. "Somebody is going to be the iPhone" of quantum, he said, although along the way there may be a couple Apple Newtons, too, he quipped.

Even an Apple Newton of quantum will be a breakthrough. "It will be solving real problems," he said.

Also: All that glitters is not quantum AI

In the meantime, handling the complexity that's cropping up now, with things like ETL, suggests there's a role for a young company that can be for quantum what Oracle was for structured query language.

"You build that out, and you have best practices, and you can become a great company, and that's what we aspire to," he said.

Zapata has fifty-eight employees and has had contract revenue since its first year of operations, and has doubled each year, said Savoie.

Read more:
Quantum computing now is a bit like SQL was in the late 80s: Wild and wooly and full of promise - ZDNet