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If someone asked you to picture a quantum computer, what would you see in your mind?

Maybe you see a normal computer-- just bigger, with some mysterious physics magic going on inside? Forget laptops or desktops. Forget computer server farms. A quantum computer is fundamentally different in both the way it looks, and ,more importantly, in the way it processes information.

There are currently several ways to build a quantum computer. But lets start by describing one of the leading designs to help explain how it works.

Imagine a lightbulb filament, hanging upside down, but its the most complicated light youve ever seen. Instead of one slender twist of wire, it has organized silvery swarms of them, neatly braided around a core. They are arranged in layers that narrow as you move down. Golden plates separate the structure into sections.

The outer part of this vessel is called the chandelier. Its a supercharged refrigerator that uses a special liquified helium mix to cool the computers quantum chip down to near absolute zero. Thats the coldest temperature theoretically possible.

At such low temperatures, the tiny superconducting circuits in the chip take on their quantum properties. And its those properties, as well soon see, that could be harnessed to perform computational tasks that would be practically impossible on a classical computer.

Traditional computer processors work in binarythe billions of transistors that handle information on your laptop or smartphone are either on (1) or theyre off (0). Using a series of circuits, called gates, computers perform logical operations based on the state of those switches.

Classical computers are designed to follow specific inflexible rules. This makes them extremely reliable, but it also makes them ill-suited for solving certain kinds of problemsin particular, problems where youre trying to find a needle in a haystack.

This is where quantum computers shine.

If you think of a computer solving a problem as a mouse running through a maze, a classical computer finds its way through by trying every path until it reaches the end.

What if, instead of solving the maze through trial and error, you could consider all possible routes simultaneously?

Quantum computers do this by substituting the binary bits of classical computing with something called qubits. Qubits operate according to the mysterious laws of quantum mechanics: the theory that physics works differently at the atomic and subatomic scale.

The classic way to demonstrate quantum mechanics is by shining a light through a barrier with two slits. Some light goes through the top slit, some the bottom, and the light waves knock into each other to create an interference pattern.

But now dim the light until youre firing individual photons one by oneelementary particles that comprise light. Logically, each photon has to travel through a single slit, and theyve got nothing to interfere with. But somehow, you still end up with an interference pattern.

Heres what happens according to quantum mechanics: Until you detect them on the screen, each photon exists in a state called superposition. Its as though its traveling all possible paths at once. That is, until the superposition state collapses under observation to reveal a single point on the screen.

Qubits use this ability to do very efficient calculations.

For the maze example, the superposition state would contain all the possible routes. And then youd have to collapse the state of superposition to reveal the likeliest path to the cheese.

Just like you add more transistors to extend the capabilities of your classical computer, you add more qubits to create a more powerful quantum computer.

Thanks to a quantum mechanical property called entanglement, scientists can push multiple qubits into the same state, even if the qubits arent in contact with each other. And while individual qubits exist in a superposition of two states, this increases exponentially as you entangle more qubits with each other. So a two-qubit system stores 4 possible values, a 20-qubit system more than a million.

So what does that mean for computing power? It helps to think about applying quantum computing to a real world problem: the one of prime numbers.

A prime number is a natural number greater than 1 that can only be divided evenly by itself or 1.

While its easy to multiply small numbers into giant ones, its much harder to go the reverse direction; you cant just look at a number and tell its factors. This is the basis for one of the most popular forms of data encryption, called RSA.

You can only decrypt RSA security by factoring the product of two prime numbers. Each prime factor is typically hundreds of digits long, and they serve as unique keys to a problem thats effectively unsolvable without knowing the answers in advance.

In 1995, M.I.T. mathematician Peter Shor, then at AT&T Bell Laboratories, devised a novel algorithm for factoring prime numbers whatever the size. One day, a quantum computer could use its computational power, and Shors algorithm, to hack everything from your bank records to your personal files.

In 2001, IBM made a quantum computer with seven qubits to demonstrate Shors algorithm. For qubits, they used atomic nuclei, which have two different spin states that can be controlled through radio frequency pulses.

This wasnt a great way to make a quantum computer, because its very hard to scale up. But it did manage to run Shors algorithm and factor 15 into 3 and 5. Hardly an impressive calculation, but still a major achievement in simply proving the algorithm works in practice.

Even now, experts are still trying to get quantum computers to work well enough to best classical supercomputers.

That remains extremely challenging, mostly because quantum states are fragile. Its hard to completely stop qubits from interacting with their outside environment, even with precise lasers in supercooled or vacuum chambers.

Any noise in the system leads to a state called decoherence, where superposition breaks down and the computer loses information.

A small amount of error is natural in quantum computing, because were dealing in probabilities rather than the strict rules of binary. But decoherence often introduces so much noise that it obscures the result.

When one qubit goes into a state of decoherence, the entanglement that enables the entire system breaks down.

So how do you fix this? The answer is called error correction--and it can happen in a few ways.

Error Correction #1:A fully error-corrected quantum computer could handle common errors like bit flips, where a qubit suddenly changes to the wrong state.

To do this you would need to build a quantum computer with a few so-called logical qubits that actually do the math, and a bunch of standard qubits that correct for errors.

It would take a lot of error-correcting qubitsmaybe 100 or so per logical qubit--to make the system work. But the end result would be an extremely reliable and generally useful quantum computer.

Error Correction #2:Other experts are trying to find clever ways to see through the noise generated by different errors. They are trying to build what they call Noisy intermediate-scale quantum computers using another set of algorithms.

That may work in some cases, but probably not across the board.

Error Correction #3: Another tactic is to find a new qubit source that isnt as susceptible to noise, such as topological particles that are better at retaining information. But some of these exotic particles (or quasi-particles) are purely hypothetical, so this technology could be years or decades off.

Because of these difficulties, quantum computing has advanced slowly, though there have been some significant achievements.

In 2019, Google used a 54-qubit quantum computer named Sycamore to do an incredibly complex (if useless) simulation in under 4 minutesrunning a quantum random number generator a million times to sample the likelihood of different results.

Sycamore works very differently from the quantum computer that IBM built to demonstrate Shors algorithm. Sycamore takes superconducting circuits and cools them to such low temperatures that the electrical current starts to behave like a quantum mechanical system. At present, this is one of the leading methods for building a quantum computer, alongside trapping ions in electric fields, where different energy levels similarly represent different qubit states.

Sycamore was a major breakthrough, though many engineers disagree exactly how major. Google said it was the first demonstration of so-called quantum advantage: achieving a task that would have been impossible for a classical computer.

It said the worlds best supercomputer would have needed 10,000 years to do the same task. IBM has disputed that claim.

At least for now, serious quantum computers are a ways off. But with billions of dollars of investment from governments and the worlds biggest companies, the race for quantum computing capabilities is well underway. The real question is: how will quantum computing change what a computer actually means to us. How will it change how our electronically connected world works? And when?

Original post:
How Does a Quantum Computer Work? - Scientific American

Marissa Giustina, a researcher with Google's quantum computer lab, draws a diagram showing "quantum supremacy" as only an early step on a path of quantum computer progress.

After years of development, quantum computers reached a level of sophistication in 2021 that emboldened commercial customers to begin dabbling with the radical new machines. Next year, the business world may be ready to embrace them more enthusiastically.

BMW is among the manufacturing giants that sees the promise of the machines, which capitalize on the physics of the ultrasmall to soar over some limits of conventional computers. Earlier this month, the German auto giant chose four winners in a contest it hosted with Amazon to spotlight ways the new technology could help the automaker.

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The carmaker found quantum computers have potential to optimize the placement of sensors on cars, predict metal deformation patterns and employ AI in quality checks.

"We at the BMW Group are convinced that future technologies such as quantum computing have the potential to make our products more desirable and sustainable," Peter Lehnert, who leads BMW's research group, said in a statement.

BMW isn't alone in its determination to evaluate the practical application of quantum computers. Aerospace giant Airbus, financial services company PayPal and consumer electronics maker LG Electronics are among the commercial businesses looking to use the machines to refine materials science, streamline logistics and monitor payments.

For years, researchers worked on quantum computers as more or less conceptual projects that take advantage of qubits, data processing elements that can hold more than the two states that are handled by transistors found in conventional computers. Even as they improved, quantum computers were best suited for research projects, some as basic as figuring out how to program the exotic machines. But at the current rate of progress, they'll soon become powerful enough to tackle computing jobs out of reach of conventional computers.

Like cloud computing before it, quantum computing will be a service that most corporations rent from other companies. The rigs require constant attention and are notoriously fiddly. Though more work is required to tap their full potential, quantum computers are becoming more and more stable, a development that's helping corporations overcome initial hesitance.

Georges-Olivier Reymond, chief executive of startup Pasqal, says the progress is turning around skeptics who previously viewed quantum computing as a fantasy. A few years ago, employees at large corporations would roll their eyes when he brought up the subject, but that's changed, Reymond says.

"Now each time I talk to them I have a positive answer," Reymond said. "They are ready to engage."

One new customer is European defense contractor Thales, which is interested in quantum computing applications in sensors and communications. "Pasqal's quantum processors can efficiently address large size problems that are completely out of reach of classical computing systems," Thales Chief Technology Officer Bernhard Quendtsaid in a statement.

Of course, quantum computing is still a tiny fraction of the traditional computing market, but it's growing fast. About $490 million was spent on quantum computers, software and services in 2021, Hyperion Research analyst Bob Sorensen said at the Q2B conference held by quantum computing software company QC Ware in December. He expects spending to grow by 22% to $597 million in 2022 and at an average of 26% a year through 2024. By comparison, spending on conventional computing is expected to rise 4% in 2021 to $3.8 trillion, Gartner analysts predict.

The growing commercial activity is notable given that using a quantum computer costs $3,000 to $5,000 per hour, according to Jean-Francois Bobier, an analyst at Boston Consulting Group. A conventional, high-performance computer hosted on a cloud service costs a half penny for the same amount of time.

Analysts say the real spending on quantum computing will start when the industry tackles error correction, a solution to the vexing problem of easily perturbed qubits that derail calculations. The fidelity of a single computing step on the most advanced machines is around 99.9%, leaving a degree of flakiness that makes a raw quantum computing calculation unreliable. As a result, quantum computers have to run the same calculation many times to provide confidence that the answer is correct.

Once error correction is mature, the revenue generated through quantum computing will explode, according to Boston Consulting Group. With today's machines, that value will likely total between $5 billion and $10 billion by 2025, according to the consultancy's estimates. Once error corrected machines arrive, the total could leap forward to hit $450 billion to $850 billion by 2040.

Software and services that hide the complexity of quantum computers also will boost usage. IonQ CEO Peter Chapman predicts that in 2022, developers will be able to easily train their AI models with quantum computers. "You don't need to know anything about quantum," Chapman said. "You just give it the data set and it spits back a model."

Among the signs of commercial interest:

Quantum computers today are more of a luxury than a necessity. But with their potential to transform materials science, shipping, financial services and product design, it's not a surprise companies like BMW are investing. The automaker stands to benefit from knowing better how materials will deform in a crash or training its vehicles' vision AI faster. Though quantum computers might not produce a payoff this year or next, there's a cost to missing out on the technology once it matures.

Read this article:
Quantum computers are on the path to solving bigger problems for BMW, LG and others - CNET

A team of researchers with Japan's NTT Corporation, the Tokyo University, and the RIKEN research center have announced the development of a full photonics-based approach to quantum computing. Taking advantage of the quantum properties of squeezed light sources, the researchers expect their work to pave the road towards faster and easier deployments of quantum computing systems, avoiding many practical and scaling pitfalls of other approaches. Furthermore, the team is confident their research can lead towards the development of rack-sized, large-scale quantum computing systems that are mostly maintenance-free.

The light-based approach in itself brings many advantages compared to traditional quantum computing architectures, which can be based on a number of approaches (trapped ions, silicon quantum dots, and topological superconductors, just to name a few). However, all of these approaches are somewhat limited from a physics perspective: they all need to employ electronic circuits, which leads to Ohmic heating (the waste heat that results from electrical signals' trips through resistive semiconductor wiring). At the same time, photonics enable tremendous improvements in latency due to data traveling at the speed of light.

Photonics-based quantum computing takes advantage of emerging quantum properties in light. The technical term here is squeezing the more squeezed a light source is, the more quantum behavior it demonstrates. While a minimum squeezing level of over 65% was previously thought required to unlock the necessary quantum properties, the researchers achieved a higher, 75% factor in their experiments. In practical terms, their quantum system unlocks a higher than 6 THz frequency band, thus taking advantage of the benefits of photonics for quantum computing without decreasing the available broadband to unusable levels.

The researchers thus expect their photonics-based quantum design to enable easier deployments there's no need for exotic temperature controls (essentially sub-zero freezers) that are usually required to maintain quantum coherence on other systems. Scaling is also made easier and simplified: there's no need to increase the number of qubits by interlinking several smaller, coherent quantum computing units. Instead, the number of qubits (and thus the performance of the system) can be increased by continuously dividing light into "time segments" and encoding different information in each of these segments. According to the team, this method allows them to "easily increase the number of qubits on the time axis without increasing the size of the equipment."

All of these elements combined allow for a reduction in required raw materials while doing away with the complexity of maintaining communication and quantum coherence between multiple, small quantum computing units. The researchers will now focus on actually building the photonics-based quantum computer. Considering how they estimate their design can scale up towards "millions of qubits," their contributions could enable a revolutionary jump in quantum computation that skips the expected "long road ahead" for useful qubit counts to be achieved.

Read more:
Research Opens the Door to Fully Light-Based Quantum Computing - Tom's Hardware

From quantum discoveries to the first AI-discovered drug candidates going into clinical trials, 2021 was a landmark year for deeptech in Europe.

Swedish battery maker Northvolt now has huge investment from companies like Volvo and VW to build gigafactories, and even ideas like Energy Vault (storing grid energy as huge stacked-up concrete blocks) which may have seemed out there a few years ago, are getting real investment.

Quantum computing took a big leap forward, with many top academics and even former White House officials, joining startups and a huge funding boost from the French and German governments. Even places like Finland built their first quantum computer.

So, what more will 2022 bring?

Investors believe that 2022 will be the year of deeptech with many more VCs and corporations jumping in to fund startups, especially as other sectors become overheated and overcrowded.

Ewan Kirk, tech entrepreneur and founder of Cantab Capital Partners, says that consumer tech like fintech, social media and ride-sharing has ridden a wave of interest, but that these businesses are hard to defend and new competition is entering the market all the time. Which starts to make deeptech look a lot more attractive.

Deeptech businesses are fundamentally different at their base, they are about leveraging a technological or scientific breakthrough, which is defensible through IP. Many VCs are starting to see that this makes them a very strong investment proposition.

Benjamin Joffe, partner at SOSV, says more funding will help startups overcome the multiple transitions they need to make from lab to market.

But what specific developments can we look forward to? Quantum computing, fusion energy and healthtech feature heavily in our experts predictions:

In 2022 we will see the first quantum computing companies demonstrating that they have solutions that are competitive with classical only computing clusters, for applications useful to society as whole even if its with a relatively narrow focus to start with. The metric is a mix of time to solution, accuracy and energy consumption. At a minimum we will have a clear vision of the requirements and scaling laws to make it happen within the next two years.

Christophe Jurczak, founder and partner at Quontonation

2022 will be a breakthrough year for quantum computing and we will finally develop material and technology enabling robust qubits. Quantum computing is a hot topic, but in reality we are very early in developing basic hardware required for the quantum computing dream to materialise.

Quantum computing depends on availability of very specific hardware and material that is able to maintain spin states of qubits for extended period of time. Due to lack of such material the qubits that we have at this point are unstable and highly prone to error, not capable of making more complex calculations with certainty. To unleash the massive potential of quantum computing we need systems with millions of stable qubits rather than the 10s of not-so-robust ones we have at this point.

Marcin Hejka, cofounder and general partner at OTB Ventures

As it stands, the most common approach to improving battery chemistry is through trial and error. Even AI and simulation technologies increasingly used to accelerate the process of identifying and cycling through potentially winning combinations are limited in their impact by the capabilities of computers.

In 2022, there will be huge steps forward as quantum computing begins solving key problems in battery materials modelling that are simply beyond the reach of standard computers, unlocking higher-performance and lower-cost batteries.

2022 will be the year in which government-backed funding will really take off

With significant capital now being invested in quantum computing, we will see more first case uses as innovation in hardware and software accelerates in 2022. As governments in the West begin to take notice of the huge potential applications of quantum computing, 2022 will be the year in which government-backed funding will really take off.

Moray Wright, CEO at Parkwalk Ventures

Nuclear fusion has always been a distant dream, always 30 years away from being ready to commercialise. But investors are starting to pay attention to nuclear fusion startups now, with US-based Commonwealth Fusion Systems raising more than $1.8bn in Series B funding led by Tiger Global. In Europe, nuclear fusion research has long revolved around the long-running ITER mega-project in the south of France, but now younger startups like Renaissance Fusion in Grenoble and Marvel Fusion in Munich are leapfrogging this with new approaches.

Ilkka Kivimaki, partner at Maki.vc

I think we are seeing the tail end of the AI and machine learning wave

I think we are seeing the tail end of the AI and machine learning wave. While it is incredibly important, it is now very much a part of modern technology development, rather than a special formula for the next big company. The focus will instead be on how we can neutralise the dual threats of climate change and future pandemics.

Ewan Kirk, founder of Cantab Capital Partners and tech entrepreneur

Chip shortages revealed the weakness of supply chains and tech sovereignty. It will become more crucial to have key suppliers located within your own country or region.

Benjamin Joffe, partner at SOSV

The light that Covid has shone on the health sector wont go away, and big investment will continue to be made here particularly in increasing the throughput of labs, from simple upgrades to the way in which data is collated, recorded and shared through to transforming the benchtop equipment itself with more flexible hardware.

Well also see more investment in further understanding complex and heterogeneous diseases; now we have the ability to retrieve and combine information from multiple genomics sources, we expect that machine learning algorithms will naturally have a bigger role to play in interpreting all the distinct layers of information and correlating findings with relevant medical knowledge (which will be particularly challenging when dealing with new variants or new genes not previously associated with a specific disease).

Zoe Chambers, partner at Frontline Ventures

The science equity industry is an emerging one but it is picking up pace. In 2022 it will continue growing since it is a main transformational engine for the European economy, and around 100 new industrial science-based companies will be set up in Europe.

Almudena Trigo Lorenzo, founding partner and chair at BeAble Capital

Here is the original post:
2022 will be the year of deeptech say investors - Sifted

2021 was quite a year, and during the first few days of 2022, I suddenly realized something.

Even in the face of this centurys worst health epidemic, technological progress has hardly missed a beat.

The entire planet has been under threat of intermittent shutdowns for multiple years now. The economy has suffered incalculable losses, and the labor market has been thrown into complete upheaval.

But despite all this, the worlds spirit of innovation and discovery is flourishing.

The real agents of change out there haven't missed a beat. If anything, this new threat has reinvigorated some of the planets top minds.

For one particular field of science, this past year has been a blockbuster.

For the past decade or more, the tech itself has been locked away in the relative safety of university labs around the world. You might have heard of it before in passing, but very few people expected it to actually materialize.

Last year, that outdated perception was shattered.

At this point, its impossible for you to NOT have heard of quantum computing. The news has been full of real-world proof that this stuff works.

In just a few decades, quantum computers have evolved from the musings of a few ambitious physicists into the genuine article.

The 2000s and 2010s saw a lot of funding shuffled around, but very little real success came out of it. The long and tedious development phase tested the resolve of even the most committed researchers.

Without a tangible success story to rile people up, the public started to gradually lose interest in the technology altogether.

Then in 2019, when Google announced it had achieved quantum supremacy, the world quickly snapped back to attention. Several competitors have since dismissed Google's claim as bogus, but the idea of quantum computers becoming the new standard was firmly established.

After that, the race was officially on. The computing industry hasn't seen so much attention from the general public since Y2K.

Everyone was asking the same question: Do they work?

Luckily, Im here to inform you that the answer is still no.

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Sure, these machines function. But they operate similarly to our current best attempts at nuclear fusion: They cost far more input than they provide in output.

By my estimate, we are somewhere between a few months and a few decades away from building a quantum machine that can rival todays top supercomputers.

I know thats a vague timeline, and I wish I could be more specific. But in the world of quantum physics, there are very few definite answers.

There is one definite figure I can offer, however: $1.02 billion.

That's the total amount of private funding that went to the young quantum computing industry in 2021 alone. And it doesn't even take into account the amount spent by deep-pocketed tech giants like IBM or Microsoft.

Some market analysts are even taking it a step further. Recent projections from reputable firms are confident that the industry will hit $1 trillion by 2030. For perspective, thats around five times more than last years global computer sales.

The takeaway here is that even without a practical prototype, the quantum computing market isn't short on cash or confidence. Hedge funds and venture capitalists are finally feeling bold enough to take the plunge.

And why shouldn't they? Even with a few daunting engineering challenges facing them, the top researchers in the field unanimously agree that it will change the world.

It wont just become a new standard it will render any old-school machines completely obsolete.

There are currently hundreds of companies that claim to be in the quantum computing business. Very few of them pass a cursory financial analysis.

Fewer still seem to have any hope of bringing a real product to market in this century.

It took some serious legwork to narrow down the best stock plays in this sector. As expected, everyone claims to have found the Holy Grail without offering anything to back it up.

After weeding out the imposters, tech editor Keith Kohl and I only feel confident recommending one top pick for this industry.

Check out the free presentation here before the rest of the rabble climbs aboard and it becomes old news.

To your wealth,

Luke SweeneyContributor, Energy and Capital

Lukes technical know-how combined with an insatiable scientific curiosity has helped uncover some of our most promising leads in the tech sector. He has a knack for breaking down complicated scientific concepts into an easy-to-digest format, while still keeping a sharp focus on the core information. His role at Angel is simple: transform piles of obscure data into profitable investment leads. When following our recommendations, rest assured that a truly exhaustive amount of research goes on behind the scenes..

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The Next Great Upgrade: 2022 and Beyond - Energy & Capital