Archive for the ‘Quantum Computer’ Category

2022 will be the year of deeptech say investors – Sifted

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

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2022 will be the year of deeptech say investors - Sifted

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

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

10 of the weirdest experiments of 2021 – Livescience.com

Every year, scientists undertake some truly baffling experiments, and 2021 was no exception. From growing mini-brains with their own eyes in petri dishes to reanimating 24,000-year-old self-replicating zombies from the Siberian permafrost, here are the absolute weirdest scientific experiments of the year.

In August, a group of scientists made news that was equal parts fascinating and horrifying when they announced they had successfully lab-grown a tiny human brain with its own pair of eyes. They made the Cronenberg-esque mini brain, called an organoid, by transforming stem cells into neural tissue, then stimulating the cells with chemical signals to form tiny rudimentary "optic cups" filled with light-sensitive cells.

Thankfully for our collective sanity and for the mini-brains themselves, the tiny organoids don't have nearly enough neural density to be conscious so they won't be asking themselves anytime soon how they awakened as a lost pair of eyes sliding around a petri dish. They are, however, incredibly useful constructs for studying brain development and potentially creating cures for retinal disorders that cause blindness something that the researchers want to study.

Read more: Lab-made mini brains grow their own sets of 'eyes'

If the Cronenburg body-horror of the last entry didn't move you, this year also saw scientists reveal an experiment more in line with Hitchcock's classic horror film "The Birds" proving that crows were smart enough to understand the concept of zero. The concept of zero, ostensibly developed by human societies somewhere in the fifth century A.D., requires abstract thinking. So it came as quite a surprise when a June paper in The Journal of Neuroscience revealed that crows not only picked zero as distinct from other numbers, but also associated it more readily with the number one than with higher numbers.

Scans of the birds' brain activity during the experiments showed that crows have specially tuned neurons for understanding the null number, but what they use those brain cells for (besides potentially plotting to take over the world, of course) is a mystery. The scientists were amazed that both human and crow brains can compute zero even though we shared our last common ancestor with birds well before the extinction of the dinosaurs; this shows that evolution takes multiple routes to create brains with the same higher-level functions.

Read more: Crows understand the 'concept of zero' (despite their bird brains)

April saw researchers finally finding the answer to one of humanity's most pressing questions: Why do Brazil nuts rise to the top of the bag? The nutty mystery was resolved by shaking a mixture of peanuts and Brazil nuts, with the Brazil nuts placed at the bottom, and taking a 3D X-ray scan of the bag after each shake. It turned out that successive shakes eventually moved the larger nuts into a vertical orientation, after which every shake forced them upwards. The scientists believe their research could help engineers design better ways to prevent size segregation from occurring in other mixtures something that, while vitally important for bags of nuts, could have essential applications in medicine and construction.

Read more: 'Brazil nut puzzle' cracked by researchers

By switching off certain genes in the daddy longlegs, scientists created a stunted "daddy shortlegs" version but why? By shortening the famous arachnid's legs, the researchers hoped to reveal the secrets behind its body plan as well as its unique method of locomotion: walking with three pairs of legs and waving the longest pair about to feel its way around.

After the gene tweak, the legs of the stunted daddy shortlegs had not only changed in size, but also in shape; they morphed into short food-manipulating appendages called pedipalps. This offered the scientists a glimpse back in time at the kinds of creatures that daddy longlegs could have evolved from 400 million years ago. And this isn't the last mutant arachnid the scientists want to create; they also plan to mutate spider fangs to glean similar insights into their evolution.

Read more: Mutant 'daddy shortlegs' created in a lab

From early antiquity all the way to the 17th century, alchemists were obsessed with the philosopher's stone: a mythical substance with the power to transmute lead into gold. In July, scientists reported an experiment that looked a little like the fabled process: for just a few fleeting seconds, they were able to transform water into a shiny, golden metal. The researchers achieved this by mixing the water with sodium and potassium metals which donate their extra electrons to the water, and therefore make the water's electrons wander freely, rendering it metallic. The briefly metallic water they created could provide scientists with some key insights into the highly-pressurized hearts of planets, where water could be squished so intensely that this process occurs naturally.

Read more: Scientists transform water into shiny, golden metal

In July, researchers working with Google revealed that they had created a time crystal inside the heart of the tech giant's quantum computer, Sycamore. The crystal was a completely new phase of matter that the researchers claimed was able to evade the second law of thermodynamics, which dictates that entropy, or the disorder of a system, must always increase. Unlike other systems, which see their entropy increase over time, the time crystal's entropy did not increase no matter how many times it was pulsed with a laser. The truly remarkable thing about the weird quantum crystals is that they are the first objects to break a fundamental symmetry of the universe, called discrete time-translation symmetry. Scientists are hoping to use the otherworldly crystals to test the boundaries of quantum mechanics the strange rules that govern the world of the very small.

Read more: Otherworldly 'time crystal' made inside Google quantum computer could change physics forever

If you were to find a group of zombies from the Pleistocene epoch frozen inside Siberian permafrost, reviving and cloning them is probably not high on your agenda. However, that's exactly what scientists described in a June paper published in the journal Current Biology. Thankfully, these zombies aren't the shambling, fictitious brain-eaters popularized by George Romero, but are instead tiny multicellular organisms called bdelloid rotifers. Once thawed, the tiny creatures began reproducing asexually through a process called parthenogenesis, creating perfect clones of themselves. Remarkably, analysis of the soil around the creatures showed that they had been frozen for 24,000 years, and they had survived by putting themselves inside a protective stasis called cryptobiosis. Scientists are hoping to study this clever trick to better understand cryopreservation and how it could be adapted for humans.

Read more: 24,000-year-old 'zombies' revived and cloned from Arctic permafrost

In May, scientists working off the coast of Japan used a long, thin drill called a giant piston corer to drill a 5 mile (8,000 meter) hole to the bottom of the Japan Trench. The scientists then extracted a 120-foot-long (37 m) sediment core from the bottom of the sea, hauling it all the way back up to their ship. The researchers wanted to examine the sediment core because they were searching for clues into the region's earthquake history the drill site is located very close to the epicenter of the magnitude-9.1 Tohoku-oki earthquake. The 2011 quake caused an enormous tsunami that smashed into the Fukushima Daiichi nuclear power plant and caused a devastating meltdown.

Read more: Scientists just dug the deepest ocean hole in history

A July study published in the journal Molecular Biology revealed that an already weird past study had produced even weirder unintended consequences. Decades ago, the Finnish scientist Ilkka Hanski introduced the Glanville fritillary butterfly onto the remote island of Sottunga, planning to study how a population of one species placed inside a harsh habitat could survive. Little did he know, the butterflies harbored a species of stomach-bursting parasitic wasp, and those wasps also carried their own, smaller, stomach-bursting hyperparasite itself a parasitic wasp. Once the butterflies were released on Sottunga, the wasps erupted, spreading across the island with their hosts. This experiment provided later scientists with not only a fascinating ecological study, but also a clear warning that we must understand the ecological webs that form around endangered species before introducing them into new environments.

Read more: 'Russian doll' set of stomach-bursting parasites released inside butterfly on remote Finnish island

Okay, so this one wasn't done by a scientist, but it's by far one of the weirdest amatuer experiments we've heard this year. A January study in the Journal of the Academy of Consultation-Liaison Psychiatry revealed that a man who had brewed a "magic mushroom" tea and injected it into his body ended up in the emergency room with the fungus growing in his blood. After injecting the psilocybin tea, the man, who had hoped to relieve symptoms of bipolar disorder and opioid dependence, quickly became lethargic, his skin turned yellow and he started vomiting blood. The man survived, but needed to take antibiotics and antifungal drugs to remove the psychoactive fungus from his bloodstream. He also had to be put onto a respirator. A growing body of research indicates that psilocybin, the psychoactive compound found in magic mushrooms, could be a promising treatment for depression, anxiety and substance abuse but only if taken safely.

Read more: 'Magic mushrooms' grow in man's blood after injection with shroom tea

Originally published on Live Science.

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Breaking Up Tech Is a Gift to China – The Wall Street Journal

Few issues unite both sides of the political divide more than anger at U.S. tech companies, whether for censorship of conservative viewpoints or for failing to counter misinformation online. In response to these concerns, legislation introduced in Congress would weaken the U.S. tech industry, ostensibly in the name of breaking up monopolies. Unfortunately, the various bills would hurt the U.S. and strengthen the hand of our greatest geopolitical rival, the Peoples Republic of China.

As of 2018, nine of the top 20 global technology firms by valuation were based in China. President Xi Jinping has stated his intention to spend $1.4 trillion by 2025 to surpass the U.S. in key technology areas, and the Chinese government aggressively subsidizes national champion firms. Beginning with the Made in China 2025 initiative, Beijing has made clear that it wont stop until it dominates technologies such as quantum computing, artificial intelligence, autonomous systems and more. Last month the National Counterintelligence and Security Center warned that these are technologies where the stakes are potentially greatest for U.S. economic and national security.

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Breaking Up Tech Is a Gift to China - The Wall Street Journal

What Can We Do with a Quantum Computer? – Ideas …

When I was in middle school, I read a popular book about programming in BASIC (which was the most popular programming language for beginners at that time). But it was 1986, and we did not have computers at home or school yet. So, I could only write computer programs on paper, without being able to try them on an actual computer.

Surprisingly, I am now doing something similarI am studying how to solve problems on a quantum computer. We do not yet have a fully functional quantum computer. But I am trying to figure out what quantum computers will be able to do when we build them.

The story of quantum computers begins in 1981 with Richard Feynman, probably the most famous physicist of his time. At a conference on physics and computation at the Massachusetts Institute of Technology, Feynman asked the question: Can we simulate physics on a computer?

The answer wasnot exactly. Or, more preciselynot all of physics. One of the branches of physics is quantum mechanics, which studies the laws of nature on the scale of individual atoms and particles. If we try to simulate quantum mechanics on a computer, we run into a fundamental problem. The full description of quantum physics has so many variables that we cannot keep track of all of them on a computer.

If one particle can be described by two variables, then to describe the most general state of n particles, we need 2n variables. If we have 100 particles, we need 2100 variables, which is roughly 1 with 30 zeros. This number is so big that computers will never have so much memory.

By itself, this problem was nothing newmany physicists already knew that. But Feynman took it one step further. He asked whether we could turn this problem into something positive: If we cannot simulate quantum physics on a computer, maybe we can build a quantum mechanical computerwhich would be better than the ordinary computers?

This question was asked by the most famous physicist of the time. Yet, over the next few years, almost nothing happened. The idea of quantum computers was so new and so unusual that nobody knew how to start thinking about it.

But Feynman kept telling his ideas to others, again and again. He managed to inspire a small number of people who started thinking: what would a quantum computer look like? And what would it be able to do?

Quantum mechanics, the basis for quantum computers, emerged from attempts to understand the nature of matter and light. At the end of the nineteenth century, one of the big puzzles of physics was color.

The color of an object is determined by the color of the light that it absorbs and the color of the light that it reflects. On an atomic level, we have electrons rotating around the nucleus of an atom. An electron can absorb a particle of light (photon), and this causes the electron to jump to a different orbit around the nucleus.

In the nineteenth century, experiments with heated gasses showed that each type of atom only absorbs and emits light of some specific frequencies. For example, visible light emitted by hydrogen atoms only consists of four specific colors. The big question was: how can we explain that?

Physicists spent decades looking for formulas that would predict the color of the light emitted by various atoms and models that would explain it. Eventually, this puzzle was solved by Danish physicist Niels Bohr in 1913 when he postulated that atoms and particles behave according to physical laws that are quite different from what we see on a macroscopic scale. (In 1922, Bohr, who would become a frequent Member at the Institute, was awarded a Nobel Prize for this discovery.)

To understand the difference, we can contrast Earth (which is orbiting around the Sun) and an electron (which is rotating around the nucleus of an atom). Earth can be at any distance from the Sun. Physical laws do not prohibit the orbit of Earth to be a hundred meters closer to the Sun or a hundred meters further. In contrast, Bohrs model only allows electrons to be in certain orbits and not between those orbits. Because of this, electrons can only absorb the light of colors that correspond to a difference between two valid orbits.

Around the same time, other puzzles about matter and light were solved by postulating that atoms and particles behave differently from macroscopic objects. Eventually, this led to the theory of quantum mechanics, which explains all of those differences, using a small number of basic principles.

Quantum mechanics has been an object of much debate. Bohr himself said, Anyone not shocked by quantum mechanics has not yet understood it. Albert Einstein believed that quantum mechanics should not be correct. And, even today, popular lectures on quantum mechanics often emphasize the strangeness of quantum mechanics as one of the main points.

But I have a different opinion. The path of how quantum mechanics was discovered was very twisted and complicated. But the end result of this path, the basic principles of quantum mechanics, is quite simple. There are a few things that are different from classical physics and one has to accept those. But, once you accept them, quantum mechanics is simple and natural. Essentially, one can think of quantum mechanics as a generalization of probability theory in which probabilities can be negative.

In the last decades, research in quantum mechanics has been moving into a new stage. Earlier, the goal of researchers was to understand the laws of nature according to how quantum systems function. In many situations, this has been successfully achieved. The new goal is to manipulate and control quantum systems so that they behave in a prescribed way.

This brings the spirit of research closer to computer science. Alan Key, a distinguished computer scientist, once characterized the difference between natural sciences and computer science in the following way. In natural sciences, Nature has given us the world, and we just discovered its laws. In computers, we can stuff the laws into it and create the world. Experiments in quantum physics are now creating artificial physical systems that obey the laws of quantum mechanics but do not exist in nature under normal conditions.

An example of such an artificial quantum system is a quantum computer. A quantum computer encodes information into quantum states and computes by performing quantum operations on it.

There are several tasks for which a quantum computer will be useful. The one that is mentioned most frequently is that quantum computers will be able to read secret messages communicated over the internet using the current technologies (such as RSA, Diffie-Hellman, and other cryptographic protocols that are based on the hardness of number-theoretic problems like factoring and discrete logarithm). But there are many other fascinating applications.

First of all, if we have a quantum computer, it will be useful for scientists for conducting virtual experiments. Quantum computing started with Feynmans observation that quantum systems are hard to model on a conventional computer. If we had a quantum computer, we could use it to model quantum systems. (This is known as quantum simulation.) For example, we could model the behavior of atoms and particles at unusual conditions (for example, very high energies that can be only created in the Large Hadron Collider) without actually creating those unusual conditions. Or we could model chemical reactionsbecause interactions among atoms in a chemical reaction is a quantum process.

Another use of quantum computers is searching huge amounts of data. Lets say that we have a large phone book, ordered alphabetically by individual names (and not by phone numbers). If we wanted to find the person who has the phone number 6097348000, we would have to go through the whole phone book and look at every entry. For a phone book with one million phone numbers, it could take one million steps. In 1996, Lov Grover from Bell Labs discovered that a quantum computer would be able to do the same task with one thousand steps instead of one million.

More generally, quantum computers would be useful whenever we have to find something in a large amount of data: a needle in a haystackwhether this is the right phone number or something completely different.

Another example of that is if we want to find two equal numbers in a large amount of data. Again, if we have one million numbers, a classical computer might have to look at all of them and take one million steps. We discovered that a quantum computer could do it in a substantially smaller amount of time.

All of these achievements of quantum computing are based on the same effects of quantum mechanics. On a high level, these are known as quantum parallelism and quantum interference.

A conventional computer processes information by encoding it into 0s and 1s. If we have a sequence of thirty 0s and 1s, it has about one billion of possible values. However, a classical computer can only be in one of these one billion states at the same time. A quantum computer can be in a quantum combination of all of those states, called superposition. This allows it to perform one billion or more copies of a computation at the same time. In a way, this is similar to a parallel computer with one billion processors performing different computations at the same timewith one crucial difference. For a parallel computer, we need to have one billion different processors. In a quantum computer, all one billion computations will be running on the same hardware. This is known as quantum parallelism.

The result of this process is a quantum state that encodes the results of one billion computations. The challenge for a person who designs algorithms for a quantum computer (such as myself) is: how do we access these billion results? If we measured this quantum state, we would get just one of the results. All of the other 999,999,999 results would disappear.

To solve this problem, one uses the second effect, quantum interference. Consider a process that can arrive at the same outcome in several different ways. In the non-quantum world, if there are two possible paths toward one result and each path is taken with a probability , the overall probability of obtaining this result is += . Quantumly, the two paths can interfere, increasing the probability of success to 1.

Quantum algorithms combine these two effects. Quantum parallelism is used to perform a large number of computations at the same time, and quantum interference is used to combine their results into something that is both meaningful and can be measured according to the laws of quantum mechanics.

The biggest challenge is building a large-scale quantum computer. There are several ways one could do it. So far, the best results have been achieved using trapped ions. An ion is an atom that has lost one or more of its electrons. An ion trap is a system consisting of electric and magnetic fields, which can capture ions and keep them at locations. Using an ion trap, one can arrange several ions in a line, at regular intervals.

One can encode 0 into the lowest energy state of an ion and 1 into a higher energy state. Then, the computation is performed using light to manipulate the states of ions. In an experiment by Rainer Blatts group at the University of Innsbruck, Austria, this has been successfully performed for up to fourteen ions. The next step is to scale the technology up to a bigger number of trapped ions.

There are many other paths toward building a quantum computer. Instead of trapped ions, one can use electrons or particles of lightphotons. One can even use more complicated objects, for example, the electric current in a superconductor. A very recent experiment by a group led by John Martinis of the University of California, Santa Barbara, has shown how to perform quantum operations on one or two quantum bits with very high precision from 99.4% to 99.92% using the superconductor technology.

The fascinating thing is that all of these physical systems, from atoms to electric current in a superconductor, behave according to the same physical laws. And they all can perform quantum computation. Moving forward with any of these technologies relates to a fundamental problem in experimental physics: isolating quantum systems from environment and controlling them with high precision. This is a very difficult and, at the same time, a very fundamental task and being able to control quantum systems will be useful for many other purposes.

Besides building quantum computers, we can use the ideas of information to think about physical laws in terms of information, in terms of 0s and 1s. This is the way I learned quantum mechanicsI started as a computer scientist, and I learned quantum mechanics by learning quantum computing first. And I think this is the best way to learn quantum mechanics.

Quantum mechanics can be used to describe many physical systems, and in each case, there are many technical details that are specific to the particular physical system. At the same time, there is a common set of core principles that all of those physical systems obey.

Quantum information abstracts away from the details that are specific to a particular physical system and focuses on the principles that are common to all quantum systems. Because of that, studying quantum information illuminates the basic concepts of quantum mechanics better than anything else. And, one day, this could become the standard way of learning quantum mechanics.

For myself, the main question still is: how will quantum computers be useful? We know that they will be faster for many computational tasks, from modeling nature to searching large amounts of data. I think there are many more applications and, perhaps, the most important ones are still waiting to be discovered.

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What Can We Do with a Quantum Computer? - Ideas ...