When we study physics one thing that we are always told, is that it is definite. Either it can be something it or it cannot be. Right?
Wrong. As opposed to the Newtonian theory of light’s nature as a particle, in the late 19th century, Albert Einstein revived light’s wave nature. The nature of light as the wave was proposed by Huygens but was dismissed because of Newton’s reputation. However, later it was established that light is “both a particle and a wave”, its essential theory was further evolved from electromagnetics into quantum mechanics.
If you did not understand anything that’s written above just skip the jargons and read along with the wonderful manifestation of quantum physics in computing. Here is the simple definition of the concept behind Quantum Computing.
The data is stored in a computer in the Boolean form, i.e in sets of 0 and 1. All digital circuits that we have presently are all dependent on this Boolean concept of data storage. You can say that all the computer circuitry that we have today, understands boolean logic; that is the manifestation of data and information in 0s and 1s.
Quantum Computing challenges the present advances in digital electronics technology. Now data can exist in multiple bits, anything between 0 and 1.
Here is an example to illustrate it:
The lowest unit of memory is a bit. (Take it analogous to cell ‘the building block for the body’). A bit can be either 1 or 0. 8 bits make 1 byte. 1024 bytes as 1KB, 1024 KBs as 1 MB and so on. So for 1 byte, there can be 16 possible combinations in which data can be stored.
For quantum computers, the smallest unit of memory is called Quantum Bit aka Qubit. A qubit can exist in both states simultaneously (0 and 1), as well as many other states in between. Now as opposed to the traditional concept Qubits can hold much more data, that gives rise to faster parallel computing.
The future is very promising as computer scientists working on quantum computers believe that it will be possible to harness these mechanisms and build computers which will be millions of times more efficient than anything available today. Here are some of the real-world problems that Quantum Computers are expected to solve.
With a lot of businesses and transactions online, the last decade had seen a 100% increase in data breaches by nefarious hacker groups holding digital businesses hostage for ransoms. Quantum computers will revolutionize data security as we see today. Even though quantum computers would be able to crack many of today’s encryption techniques, predictions are that they would create hack-proof replacements.
Even though Quantum Computers is the thing for the future, don’t expect it to be a regular home use computer. The computers that we have now is not going to go anywhere or be replaced by Quantum Computers. In fact, classical computers are better at some tasks than quantum computers (email, spreadsheets and desktop publishing to name a few).
Given the faster processing speed, Quantum computers are great for solving optimization problems. From figuring out the best way to schedule flights at an airport to determining the best routes on Google Maps things will be more efficient. Recently, Google announced its indigenous quantum computer 100 million times faster than any classical computer in its available.
Now that you have a brief idea of what a quantum computer can do, let’s see what some of its advocates have to say about this.
Satya Nadella, Microsoft CEO:
“The world is running out of computing capacity. Moore’s law is kinda running out of steam … [we need quantum computing to] create all of these rich experiences we talk about, all of this artificial intelligence.”
Seth Lloyd, author of Programming the Universe:
“A classical computation is like a solo voice – one line of pure tones succeeding each other. Quantum computation is like a symphony – many lines of tones interfering with each other.”
Jeremy O’Brien, a physicist at the University of Bristol:
“In less than 10 years quantum computers will begin to outperform everyday computers, leading to breakthroughs in artificial intelligence, the discovery of new pharmaceuticals and beyond. The very fast computing power given by quantum computers has the potential to disrupt traditional businesses and challenge our cybersecurity.”
While the world is optimistic to revolutionize a lot of things by using Quantum Computers, building one is no less than a scientific conundrum.
With the sub-polar requirement of temperatures, Quantum computing requires extremely cold temperatures, as sub-atomic particles must be as close as possible to a stationary state to be measured. The cores of D-Wave quantum computers operate at -460 degrees f, or -273 degrees c, which is 0.02 degrees away from absolute zero. So don’t be surprised if the arctic and antarctic is the next destination to claim information supremacy


Lensing caused by various analytic spacetimes. For all panels, we use Figure 3 as a background, oriented such that the camera is pointed at the white reference dot. The camera has a 60 degree feld of view and is at a distance of 15 Schwarzschild radii from the origin measured using Kerr- Schild coordinates. The top row shows Minkowski and Schwarzschild spacetimes. The bottom row shows two views of the Kerr spacetime, with dimensionless spin x = 0.95, viewed with the camera pointing parallel to the spin axis of the black hole (bottom left) and perpendicular to the spin axis (bottom right). (Credit: A. Bohn, F. Hebert, W. Throwe, D. Bunadar, K. Henriksson, M. Scheel, N. Taylor)
The difficult part of this work is calculating the trajectory of the photons using the physics of general relativity. These equations are notoriously non-linear, so physicist sometimes simplify them by assuming that a system remains constant in the time it takes for light to pass by. The difficulty with black hole binaries is that this assumption does not hold— these objects orbit so rapidly as they approach each other that space-time warps, even during the time it takes for light to pass by.
A BBH system of equal-mass black holes with no spin, viewed near merger with the orbital angular momentum out of the page. (Credit: A. Bohn, F. Hebert, W. Throwe, D. Bunadar, K. Henriksson, M. Scheel, N. Taylor)
Andy Bohn(et al.) at Cornell University in Ithaca, New York, reveals how in-spiraling black hole pairs should distort the light field around them. The team has concluded that from large distances, binaries are more or less indistinguishable from single black holes. Only a relatively close observer would be able to see the fascinating detail that they have simulating or one with very high resolving power.
The first observation of much bigger deflections, such as those produced by black holes or black hole pairs, will be something of a triumph for whoever spots them first.
via physics arxiv Like this: Like Loading...
Friday, September 19, 2014
When space probes, such as Rosetta and Cassini, fly over certain planets and moons, in order to gain momentum and travel long distances, their speed changes slightly for an unknown reason. A researcher has now analyzed whether or not a hypothetical gravitomagnetic field could have an influence. However, other factors such as solar radiation, tides, or even relativistic effects or dark matter could be behind this mystery. An artist’s rendition of Rosetta probe during a flyby. (Credit: ESA/C.Carreau) via
The starboard truss of the International Space Station while Space Shuttle Endeavour docked with the station. The newly installed Alpha Magnetic Spectrometer (AMS) is visible at center left. (Credit: NASA) via
The dome of the Blanco Telescope, which houses DECam, the 570-megapixel CCD camera used for the Dark Energy Survey, at the Cerro Tololo Inter-American Observatory in Chile. (Credit: Reidar Hahn) via
The lonely landscape of Rosetta’s comet – Comet 67P/Churyumov-Gerasimenko from a distance of just 29 kilometers (Credit: ESA) via
Mosaic of southern hemisphere of Miranda, the innermost regular satellite of Uranus, with radius of 236 km. Projection is orthographic, centered on the south pole. Visible from left to right are Elsinore, Inverness, and Arden coronae. (Credit: NASA/Jet Propulsion Laboratory/Ted Stryk) via
An international team of physicists has shown that the mass ratio between protons and electrons is the same in weak and in very strong gravitational fields. Pictured above is the laser system with which the hydrogen molecules were investigated on earth. (Credit: LaserLaB VU University Amsterdam/Wim Ubachs) via
The MIT BioSuit, a skintight spacesuit that offers improved mobility and reduced mass compared to modern gas-pressurized spacesuits. (Credit: Jose-Luis Olivares/MIT) via
mit Like this: Like Loading...
Friday, September 5, 2014
Artist impression of the Square Kilometer Array. If all goes according to plan in the next decade, we could see these small perturbations on the moon—and begin to solve some of the mysteries of space. (Credit: SKA) via
Space travelers from around the world are headed to China this month for an international Planetary Congress, which will explore the possibilities for expanding human spaceflight cooperation among different countries. Pictured above is China’s first astronaut, Yang Liwei, is now vice director of the China Manned Space Engineering Office. (Credit: CMS) via
An animation of the quicksort algorithm sorting an array of randomized values. The red bars mark the pivot element; at the start of the animation, the element farthest to the right hand side is chosen as the pivot. (Credit: RonaldH) via
Rather than keeping all its eggs in D-Wave’s basket, Google’s “Quantum A.I. Lab” announced that it is starting a collaboration with an academic quantum computing researcher, John Martinis of the University of California-Santa Barbara. (Credit: Wiki, Timmer) via
In the grasp of the Japanese robotic arm, NanoRack’s CubeSat deployer releases a pair of miniature satellites last month. (Credit: NASA) via
discovery Like this: Like Loading...


Flashes of what could become a transformative new technology shoot through a network of optical fibers beneath Chicago.
Researchers have created one of the world’s largest networks for sharing quantum information– a field of science that relies on paradoxes so strange that Albert Einstein did not believe them.
The network, which links the University of Chicago to Argonne National Laboratory in Lemont, is a rudimentary version of what scientists hope to one day become the Internet of the future. For now, it is open to businesses and researchers to test the basics of quantum information sharing.
The network was announced this week by the Chicago Quantum Exchange, which also involves the Fermi National Accelerator Laboratory, Northwestern University, the University of Illinois and the University of Wisconsin.
With $500 million in federal investment in recent years and $200 million from the state, Chicago, Urbana-Champaign and Madison are a leading region for quantum information research.
Why does this matter to the average person? Because quantum information has the potential to solve currently unsolvable problems, both threaten and protect private information, and lead to breakthroughs in agriculture, medicine and climate change.
While classical computing uses bits of information that contain a 1 or a zero, quantum bitsor qubits, are like a coin tossed in the air – they contain both a 1 and a zero, to be determined once detected.
That property of being in two or more states at once, called superposition, is one of the many paradoxes of quantum mechanics: how particles behave at the atomic and subatomic levels. It’s also a potentially critical advantage, as it can handle exponentially more complex problems.
Another important aspect is the property of entanglement, whereby qubits separated by large distances can still be correlated, so that a measurement in one place reveals a measurement far away.
The recently expanded Chicago network, created in collaboration with Toshiba, scatters light particles called photons. Trying to intercept the photons destroys them and the information they contain, making it much harder to hack.
The new network will allow researchers to “expand the boundaries of what is currently possible,” said University of Chicago professor David Awschalom, director of the Chicago Quantum Exchange.
However, researchers need to solve many practical problems before large-scale quantum computing and networks are possible.
For example, researchers at Argonne are working to create a “foundry” where reliable qubits can be forged. An example is a diamond membrane with small cells to hold and process qubits of information. Argonne researchers also created a qubit by freezing neon to hold a single electron.
Since quantum phenomena are extremely sensitive to any disturbance, they can also be used as small sensors for medical or other applications, but they also need to be made more durable.
The quantum network was launched in Argonne in 2020, but has now been extended to Hyde Park and opened for use by businesses and researchers to test new communications equipment, security protocols and algorithms. Any company that relies on secure information, such as bank financial records or hospital medical records, could potentially use such a system.
While quantum computers are now under development, they may one day be able to perform much more complex calculations than current computers, such as folding proteins, which could be useful in developing drugs to treat diseases such as Alzheimer’s disease.
In addition to stimulating research, the quantum field stimulates economic development in the region. A hardware company, EeroQ, announced in January that it is moving its headquarters to Chicago. Another local software company, Super.tech, was recently acquired and several others are starting up in the region.
Since quantum computing can be used to hack into traditional encryption, it has also attracted bipartisan attention from federal lawmakers. The National Quantum Initiative Act was signed by President Donald Trump in 2018 to accelerate quantum development for national security purposes.
In May, President Joe Biden ordered the federal agency to migrate to quantum-resistant cryptography on its most critical defense and intelligence systems.
Ironically, basic math problems, such as 5+5=10, are somewhat difficult due to quantum computer† Quantum information will likely be used for advanced applications, while classic computing will likely remain practical for many everyday uses.
The famous physicist Einstein mocked the paradoxes and uncertainties of quantum mechanics, saying that God does not “play dice” with the universe. But quantum theories have proven correct in applications from nuclear power to MRIs.
Stephen Gray, senior scientist at Argonne who is working on algorithms to run on quantum computers, said quantum work is very difficult and no one fully understands it.
But there have been significant advances in the field over the past 30 years, leading to what some scientists jokingly called Quantum 2.0, with practical advances expected over the next decade.
“We bet that in the next five to ten years there will be a real quantum advantage (over classic computing),’ said Gray. ‘We’re not there yet. Some naysayers shake their sticks and say it will never happen. But we are positive.”
Just as early work on conventional computers eventually led to cell phones, it’s hard to predict where the quantum research will lead, said Brian DeMarco, a physics professor at the University of Illinois at Urbana-Champaign who works with the Chicago Quantum Exchange.
“That’s why it’s an exciting time,” he said. “Key uses are yet to be discovered.”
2022 Chicago Tribune.
Distributed by Tribune Content Agency, LLC.
Quote: Chicago Quantum Exchange Takes First Steps Towards a Future That Could Revolutionize Computing and Medicine (2022, June 22) retrieved June 24, 2022 from https://phys.org/news/2022-06-chicago -quantum-exchange-future-revolutionize .html
This document is copyrighted. Other than fair trade for personal study or research purposes, nothing may be reproduced without written permission. The content is provided for informational purposes only.


Nobody agrees on how to build a quantum computer. Why?
There are a dizzying number of competing technologies that underlie quantum computing — and so far "it's really too early to pick a winner."
Microsoft has bet the farm on something called anyons. IBM, Intel and Google have backed superconductors. And even if those scientific words don't make much sense, at least you've heard of the organizations.
Less well-known outfits, like startups IonQ, QuEra, D-Wave, PsiQuantum and Silicon Quantum Computing, are using a range of other esoteric scientific approaches to build quantum computers.
No one involved doubts that it's worth attempting to build a machine that can process information using the strange laws that govern matter at the quantum level. But there is no consensus about how best to proceed — or who is going to get there first.
"I think it's really too early to pick a winner," says Peter Knight, senior research investigator at Imperial College London.
Quantum computers are created from processing units known as quantum bits, or qubits. As well as superconductors (which are materials with zero electrical resistance below specific low temperatures) and anyons (which are so-called "quasi-particles"; more on both below), researchers are creating qubits from ions, atoms, photons and even individual phosphorus atoms embedded in silicon, among others. Each one, as you might imagine given the lack of consensus, has its advantages and drawbacks.
Leader of the pack
At the moment, superconductors and trapped ions are widely considered the two leading options.
Google's superconducting qubits, which are loops of superconductor constricted by a "pinch" at one point — the pinch, called a Josephson Junction, gives the loop similar quantum properties to an atom — are currently considered by many to be the class leader. Late last year, they performed a computation that would take the world's most powerful supercomputer 10,000 years. Google's quantum computer, called Sycamore, did it in 3 minutes and 20 seconds. (Read more.)
It was a "very significant" milestone, according to Travis Humble, director of Oak Ridge National Laboratory's Quantum Computing Institute. "We finally had a quantum processor that needed a supercomputer to compare whether we were getting the right answer," he says. "As far as I know, that's the first time that has ever happened."
Many startups, such as Rigetti of Berkeley and Finland's IQM, share the optimism about superconducting qubits. As do IBM and Intel. But that enthusiasm and Google's result don't mean other technologies will lose their investors' interest. "My impression is that there are a few different areas generating enthusiasm, so I don't think the field has skewed too much towards Google yet," says Joe Fitzsimons, CEO of Singapore-based startup Horizon Quantum Computing.
There are some doubts about whether superconducting qubits can be built and operated in large enough numbers to make them actually useful in the long run. "The question is, how do you get to hundreds of thousands of qubits?" asks Benjamin Bloom of Berkeley-based Atom Computing.
And that really is a big question. Google's Sycamore uses just 54 qubits. But no one knows how big a truly useful quantum computer will have to be; some experts claim that 1 million qubits might be required. And because superconducting qubits need to be cooled to around -270 Celsius (-454 Fahrenheit), cooling even thousands of them could prove to be an almost insurmountable headache.
The other main contender
A strong contender to leapfrog superconductors is so-called ion traps, which are used by companies including Alpine Quantum Technologies, based in Innsbruck, Austria. In ion traps, atoms forming the basis of the qubit have an electron removed, and the ion is held in position using magnetic fields. They have a big plus in terms of practical implementation: "Ion trap systems operate at room temperature and don't require special cooling," says Thomas Monz, a co-founder of Alpine.
Monz certainly doesn't characterize Alpine as "behind" in the quantum race. He points out that it and its main competitor on this technology — IonQ, a startup spun out of the University of Maryland — are operating with more than 100 qubits that induce fewer errors than superconducting qubits. They also have established interfaces for operation and modular designs that will make scaling up feasible.
That Alpine has a device with more quibits than Google but hasn't demonstrated supremacy isn't necessarily a sign of inferiority: Performance isn't just about raw qubit numbers, and algorithms aren't easily transferred between quantum computers anyway. Instead, think about it as a different but competing technology that is maturing at a different rate, with different priorities. As Monz puts it: "What's the best computer? Do you value the small and mobile one? Or the one with the fast CPU?"
Some competitors remain unconvinced about superconductors and ion traps, despite their "frontrunner" status. "Their systems are currently almost unusable — you can only put toy problems on them," says Alan Baratz, CEO of D-Wave Systems, alluding to the currently fragile nature of the world's leading quantum computers. (D-Wave has its own unique — and controversial — approach to quantum computing hardware; see sidebar.)
Besides D-Wave, plenty of other technologies are up for the challenge. In Australia, Silicon Quantum Computing hopes that its ambitious scheme to piggyback on the well-established fabrication routines of the semiconductor industry means it can assemble qubits that are easy to manufacture at very large scales. SQC's qubits are the electrons hosted on a single phosphorus atom embedded in a silicon chip, but the company doesn't expect to have a useful general purpose quantum computer until the 2030s.
Microsoft might take even longer. Its technology, called topological quantum computing, centers on a particle called — wait for it — a non-abelian anyon. This doesn't occur naturally. It will only pop into existence in very particular circumstances, such as when strong magnetic fields are applied to ultrathin sheets of semiconductors. Not many people outside the company are sure that it can ever be created in a reliable enough way to support a technology infrastructure.
"The Microsoft bet is really interesting: It's been extraordinarily hard to make these qubits," Knight says. But, he adds, their properties could allow Microsoft's quantum computations to run without generating errors. That would mean a significant reduction in the number of qubits required because, for most of the technologies, the overwhelming majority of the qubits in a working quantum computer — at least 5 in 6 — are required exclusively for error correction. "Their approach demonstrates that when you've got serious resources, you can look at alternative platforms."
That also seems to be true of the most recent entrant to the race. In November 2019, news leaked that Palo Alto-based PsiQuantum raised $230 million to develop its photon-based qubit technology, originally developed at the University of Bristol, into a fully fledged quantum processor.
So, there are stronger contenders and underdogs, for sure, but the field is crowded — and there is no outright winner right now. But then, there may never be: The reality is that quantum computers could end up never even usurping classical machines. "If we ever use quantum computers," Humble says, "they are probably going to be integrated into our supercomputing systems."
When is a quantum computer not a quantum computer?
D-Wave Systems has been seen as a kind of bad boy of quantum computing for a few years. Its approach, known as annealing, doesn't involve operating quantum versions of logic gates. Instead, its machines allow thousands of superconducting qubits to interact in loosely defined ways. "What that means is that we can scale much more rapidly," says Alan Baratz, D-Wave's CEO.
To use a D-Wave quantum computer, you first formulate your question in a way that mirrors looking for the lowest point in a landscape. Asking the right question kicks the qubits into a high-energy state where they occupy many quantum states at once. If the question is correctly formulated, it is akin to simultaneously occupying all the points in the landscape of answers. As the qubits settle toward their lowest energy state, they reveal the lowest point in the landscape — the required answer.
Criticisms have arisen because D-Wave's is not a general purpose machine: Relatively few problems can be efficiently solved this way. Still, it has plenty of fans, including users at NASA, Volkswagen, Lockheed Martin and Oak Ridge National Laboratory. "We're seeing interesting results," says Travis Humble, director of ORNL's Quantum Computing Institute. "I can test much larger problem sizes than I could on devices that only have 50 qubits."


“Every rose has its thorn,” the song goes, but not every rose has electronic wires running through its body. The futuristic idea of plant cyborgs is making the leap from science fiction to real-world science.
What’s the big deal?
Swedish researchers have been working on ways to regulate plant growth, using electronic wires grown inside the plants own nutrient channels to host sensors and drug-delivery systems. The aim is to provide just the right amount of plant hormones at just the right time. Such efforts could provide even more precise human control over plant production and agriculture.
A separate but no less exciting project involves embedded biofuel cells that could literally turn plants into solar power plants. If all goes well, sensors and other devices could someday harvest electricity from the natural process of photosynthesis that enables plants to turn sunlight into chemical energy. It’s not often that such a sweet-smelling prospect begins with a humble garden rose. But that’s where the first successful steps toward electronic plants has begun. A team at Linköping University in Sweden has taken a huge step forward with the first experiments demonstrating electronic circuits within the living bodies of plant stems and leaves. Their research is detailed in the 20 November 2015 issue of the journal Science Advances.
They grew electronic wires as long as 10 centimeters within garden rose stems and turned leaves into patchy electronic displays capable of changing colors between light and dark on demand. They also built working transistors—the basic switches at the heart of modern electronics—based on the wires embedded within the plants.
“In a sense, we are then introducing a nervous system into the plants,” says Magnus Berggren, a professor of organic electronics at Linköping University in Sweden.
But the researchers didn’t perform Frankenstein-style surgery to implant the wires. Instead, they made use of the xylem, plants’ natural system of channels that typically carry water and nutrients from the roots to stems, leaves, and flowers.
The team’s early attempts to thread conductive polymer wires through the xylem led to the xylem being clogged or the plants exhibiting severe toxic reactions. But the researchers eventually discovered that a liquid solution containing a polymer called poly(3,4-ethylenedioxythiophene), or PEDOT, could readily be taken up by the xylem and distributed evenly throughout. What’s more, they found, it would eventually form a solid wire capable of conducting electricity. The presence of such “xylem wires” still allows the channels to carry the necessary water and nutrients for plant survival.
Berggren explained how the liquid solution containing dissolved chains of PEDOT-S:H—a chemical variation of PEDOT—was able to form solid wires with the help of both the xylem’s vascular channels and the plants’ delayed immune response:
After some time, the plant reacts against this unknown material. A common reaction against pathogens or toxic materials involves exchange of monovalent ions with divalent ones. The increase of divalent ions promote self-organization and formation of the actual conducting wires along the inner walls of the xylem channels. In a sense, the plant is helping us to separate the the event of distribution of the conducting and electronic materials from the event of film formation along the xylem walls.
Successful creation of the xylem wires also allowed the researchers to create “organic electrochemical transistors” within the plants; these transistors convert chemical signals into electronic outputs. Such transistors could form the basic hardware for more sophisticated plant cyborg devices. The team even used the plant circuitry to demonstrate digital logic gates—the building blocks for performing more complex electronic and computing operations.
Other experiments turned the leaves of roses into living electronic displays. The Swedish researchers accomplished this by encapsulating a leaf in a syringe filled with a different PEDOT solution. When the syringe’s plunger was pulled up, it created a vacuum that sucked gas out of the leaf through the “stomata” pores on the leaf surface. Once the syringe plunger was pushed down, the PEDOT solution rushed into the pores to fill the spaces between the leaf’s veins.
The result was a patchy network of conductive material within the leaf. Researchers sandwiched the leaves between PEDOT films to create electrical contacts with the PEDOT inside the leaves. That enabled the team to remotely manipulate the material within the leaves, changing their color between lighter and darker patterns. The switch between light and dark typically took about 20 seconds. The researchers observed that a pattern, whether light or dark, would remain visible for about 10 minutes.
The researchers mostly experimented with cut rose stems and leaves, but what works in garden roses could also help create other electronic plants, Berggren said. The basic structure of roses resembles those of larger plants such as trees, which means trees could also theoretically become living plant cyborgs or “e-plants.”
Jeremy Hsu has been working as a science and technology journalist in New York City since 2008. He has written on subjects as diverse as supercomputing and wearable electronics for IEEE Spectrum. When he’s not trying to wrap his head around the latest quantum computing news for Spectrum, he also contributes to a variety of publications such as Scientific American, Discover, Popular Science, and others. He is a graduate of New York University’s Science, Health & Environmental Reporting Program.


We all have an idea of how the internet works: Packets of data and communication are transmitted across interconnected devices using a routing network that follows Transport Control protocol and Internet Protocol. This data is sent electronically via copper wires, by bursts of light via optical fibers, or wirelessly via microwaves. However, the internet network as we know it is what scientists actually consider “classical.” And that’s because there is a more advanced way of securing data transfer: quantum network.
What is a Quantum Network?
A quantum network is an internet network that makes use of the properties of photons to transmit data. It allows quantum devices to exchange information within a particular environment that harnesses the principles of quantum mechanics. As such, it would be difficult to understand what a quantum network is or how quantum internet works without a basic understanding of quantum physics.
Quantum mechanics describes the physical properties of nature at the atomic (and subatomic particle) scale. In very simple terms, this branch of quantum physics governs the laws of the very small. And photons are the smallest quantum of electromagnetic fields, including light and radio waves. It is the smallest energy packet of electromagnetic radiation.
Also read: The Evolution of Data Centers Lies in Digital Transformation
How Do Quantum Networks Work?
A quantum network would allow the ultra secure transmission and exchange of quantum communications between distinct quantum endpoints or devices over fiber optic cables. Quantum devices will use their own “qubits” or quantum bits — the equivalent of bits used by ordinary computers but can be in a superposition of both ‘0’ and ‘1.’ Information is stored in these qubits, which are encoded keys that are typically polarized photons. These photons can travel very easily along fiber optic cables.
If there is an attempt to intercept the encoded keys, the delicate quantum state of the qubits will be destroyed, along with the data they hold. When such intrusion happens, the endpoints will be alerted. The ability to detect any intrusion lends the quantum network unprecedented capabilities that are rather impossible for today’s web applications to carry out.
Moreover, quantum networks apply uniquely quantum phenomena, such as no-cloning, entanglement, and superposition. These phenomena are not available to ordinary internet networks. Photons exist in a superposition of all their possible quantum states and when they are measured, they are forced to select one of these states. Unfortunately, a quantum state can’t be measured without any disturbance, thus betraying any attempt at measurement. An unknown quantum state also cannot be copied or cloned. Therefore, a well-designed quantum network is inherently safe from this behavior.
You may be wondering, though, how quantum communication can be amplified in order to reach its recipients from afar if a photon cannot be copied or duplicated. Thanks to entanglement, which is another quantum phenomenon, the range of quantum networks can be extended.
A quantum network’s main purpose is to enable qubits on one device to be entangled with the qubits on another device. This entanglement serves many potential purposes, including encryption. Measurements on entangled photons are always correlated with each other, so repeatedly reading the qubits’ quantum states allows users to create a secret code.
This correlation of entangled photons applies regardless of how far apart they are. As such, quantum network repeaters that apply entanglement to extend a quantum network’s range can be developed.
The Benefits of Quantum Networks
We have already established that quantum networks are ultra secure and are impervious to any kind of cyberhacking. Encrypted messages will be impossible to intercept.
However, aside from the assurance of security, quantum internet can transmit large volumes of information across wide distances at a much faster speed than classical networks are capable of. This could be revolutionary for apps and software, as well as for any updates they need to deploy over the air.
Also read: Networking 101: NVMe over TCP
What Sectors Will Benefit Most from Quantum Internet?
The financial sector will greatly benefit from using quantum internet, especially in securing online banking transactions. Consumers will feel safer and confident sharing personal data and doing their banking and financial activities online because of this promise of security.
Other sectors that will benefit greatly from using quantum internet include the public and healthcare sectors. A faster and safer internet will help these sectors expedite their processes and provide services promptly. Quantum computing will also allow organizations under this sector to solve complex problems and to conduct large-scale experiments and studies.
Quantum Networks Now
Quantum networks are still in the experimental stage and tech companies are still starting to build them. IT professionals, researchers, academics, and other experts in the field are still developing devices that are essential for a quantum network infrastructure, including quantum routers, gateways, hubs, repeaters, and other tools.
Also, recently, the United States Department of Energy (DOE) published the first blueprint laying out its step-by-step strategy on how to realize the quantum internet dream. It is expected that this particular project will be granted federal funding of nearly $625 million.
Quantum Networks in the Future
Once quantum internet takes off, we can expect the birth of a whole new industry. Of course, classical or ordinary internet will remain and they will exist side by side. While we can expect large organizations to utilize quantum networks to safeguard the large volume of valuable data they have in their possession, individual consumers are most likely to continue using classical internet. This isn’t surprising considering that quantum internet is a new technology and will likely be expensive in the beginning.
In addition to slow adoption because of the expense of overhauling current classic systems, there’s also the fact that it takes time for people to adapt to new technologies. This lack of urgency is also rooted in the “if-it-ain’t-broke-why-fix-it” attitude that consumers often initially have when new technologies are introduced. However, in time, quantum internet will become more accessible and more affordable to a growing number of people. The longer it is used, the more commonplace and mainstream it will become.
Read next: Networking 101: Understanding SASE


Yaniv Erlich, a core member of the New York Genome Center and associate professor of Computer Science and Computational Biology at Columbia University, holds a small three-dimensionally (3D)-printed bunny in front of his webcam. The toy, he says, is actually a storage device. "The plastic fibers in the bunny have silica beads," he says, "and inside these beads is DNA that encodes a file with instructions on how to print an exact replica of this bunny."
As with a real rabbit, the 3D-printed toy, developed with chemical engineer Robert Grass at ETH Zürich, carries its own blueprints in the DNA within it. "You can chop off any part of the bunny," Erlich explains, "and there's DNA in every piece, and you can amplify it and print a new bunny. We think we can replicate them to about 1021, or enough bunnies for everyone in the world until the end of humanity."
The project is less about toymaking than it is about the transformative potential of DNA data storage.
DNA boasts a rare combination of durability, low energy consumption, and phenomenal density. "We estimate that a DNA system could store one exabyte per cubic inch," says computer scientist Karin Strauss, a principal research manager at Microsoft. By using a DNA data storage system, she said, "What requires a whole datacenter to store today would fit in the palm of your hand."
On a basic level, DNA storage involves taking the four basic molecules in DNA—adenine, thymine, cytosine, guanine, or A, T, C, and G—and mapping them to sequences of bits, so "A" might correspond to 00 and "T" to 01. Scientists take a sequence of bits and synthesize and store DNA that represents those bits.
Strauss, computer scientist Luis Ceze of the University of Washington, and their interdisciplinary team recently developed a fully automated, end-to-end system. Previous systems required help from chemists and other scientists, but the new prototype automatically encodes the bits, makes the DNA, stores that DNA, retrieves and reads it, and then returns the data.
In the first iteration, they stored the word 'hello'. "It is by no means a high-performance system," Strauss says. "It was intended to be a first demonstration that automation in DNA data storage is indeed possible, end to end. But the maturity will improve. Eventually we could see DNA storage devices that look like racks, but with fluidics components, inside datacenters."
Strauss and Ceze recently were named to share the 2020 Maurice Wilkes Award, for their work on DNA-based digital data storage.
Another recent breakthrough focused on efficiently reading and retrieving DNA-stored data. Computer engineer James M. Tuck, chemical engineer Albert Keung, and their colleagues at North Carolina State University recently published a paper detailing their novel approach, which they call Dynamic Operations and Reusable Information Storage, or DORIS. The technique employs what they call a toehold system, in which a single-stranded piece of DNA is attached to a double-stranded section that stores data. The single strand, or toehold, effectively carries the file name, or identifying information, which allows them to efficiently search for specific DNA data. Once they retrieve a file, they make RNA copies of the DNA and its stored data, then return the original DNA to the storage medium undamaged.
Previous systems relied on more involved chemistry or molecular manipulations that could degrade the stored data in the long run.
The system holds great potential, says Tuck, for a very dense, resilient storage system. "In a relatively small space, we'd be able to store lots of information, label it with distinct addresses, and pull out the information we want while having minimal degradation on the library that's there," he says.
As for applications, the storage density and durability of DNA make it ideal for archival storage, according to Strauss, who suspects the first iterations might appear in the controlled environment of a datacenter.
Erlich has additional applications in mind. In the future, car parts could be embedded with DNA that harbors data on how to manufacture the component, should it become obsolete. An artificial knee or hip could contain a patient's relevant medical details, so doctors operating on the prosthetic in the future could easily recover important health information.
Tuck adds that it would be a waste not to find a way to compute on DNA-stored data where it resides, and Strauss and Ceze have made advances in that area. Keung, meanwhile, hopes that instead of choosing a particular system, researchers will continue to explore creative approaches.
"We are at this inflection point with how we build computers right now, with the end of Moore's Law in sight, and different efforts into quantum computing and molecular computing," says Ceze. "It's becoming increasingly clear that these approaches are all good at different things, and we need to develop this portfolio of new technologies to ensure we can continue building better computers."
Gregory Mone is a Boston-based science writer and the author, with Bill Nye, of Jack and the Geniuses: At the Bottom of the World.
No entries found


Physicists push limits of Heisenberg Uncertainty Principle
- New experiments with vibrating drums push the boundaries of quantum mechanics.
- Two teams of physicists create quantum entanglement in larger systems.
- Critics question whether the study gets around the famous Heisenberg uncertainty principle.
Recently published research pushes the boundaries of key concepts in quantum mechanics. Studies from two different teams used tiny drums to show that quantum entanglement, an effect generally linked to subatomic particles, can also be applied to much larger macroscopic systems. One of the teams also claims to have found a way to evade the Heisenberg uncertainty principle.
One question that the scientists were hoping to answer pertained to whether larger systems can exhibit quantum entanglement in the same way as microscopic ones. Quantum mechanics proposes that two objects can become “entangled,” whereby the properties of one object, such as position or velocity, can become connected to those of the other.
An experiment performed at the U.S. National Institute of Standards and Technology in Boulder, Colorado, led by physicist Shlomi Kotler and his colleagues, showed that a pair of vibrating aluminum membranes, each about 10 micrometers long, can be made to vibrate in sync, in such a way that they can be described to be quantum entangled. Kotler’s team amplified the signal from their devices to “see” the entanglement much more clearly. Measuring their position and velocities returned the same numbers, indicating that they were indeed entangled.
Evading the Heisenberg uncertainty principle?
Another experiment with quantum drums — each one-fifth the width of a human hair — by a team led by Prof. Mika Sillanpää at Aalto University in Finland, attempted to find what happens in the area between quantum and non-quantum behavior. Like the other researchers, they also achieved quantum entanglement for larger objects, but they also made a fascinating inquiry into getting around the Heisenberg uncertainty principle.
The team’s theoretical model was developed by Dr. Matt Woolley of the University of New South Wales. Photons in the microwave frequency were employed to create a synchronized vibrating pattern as well as to gauge the positions of the drums. The scientists managed to make the drums vibrate in opposite phases to each other, achieving “collective quantum motion.”
The study’s lead author, Dr. Laure Mercier de Lepinay, said: “In this situation, the quantum uncertainty of the drums’ motion is canceled if the two drums are treated as one quantum-mechanical entity.”
This effect allowed the team to measure both the positions and the momentum of the virtual drumheads at the same time. “One of the drums responds to all the forces of the other drum in the opposing way, kind of with a negative mass,” Sillanpää explained.
Theoretically, this should not be possible under the Heisenberg uncertainty principle, one of the most well-known tenets of quantum mechanics. Proposed in the 1920s by Werner Heisenberg, the principle generally says that when dealing with the quantum world, where particles also act like waves, there’s an inherent uncertainty in measuring both the position and the momentum of a particle at the same time. The more precisely you measure one variable, the more uncertainty in the measurement of the other. In other words, it is not possible to simultaneously pinpoint the exact values of the particle’s position and momentum.Heisenberg’s Uncertainty Principle Explained.Credit: Veritasium / Youtube.com
Big Think contributor astrophysicist Adam Frank, known for the 13.8 podcast, called this “a really fascinating paper as it shows that it’s possible to make larger entangled systems which behave like a single quantum object. But because we’re looking at a single quantum object, the measurement doesn’t really seem to me to be ‘getting around’ the uncertainty principle, as we know that in entangled systems an observation of one part constrains the behavior of other parts.”
Ethan Siegel, also an astrophysicist, commented, “The main achievement of this latest work is that they have created a macroscopic system where two components are successfully quantum mechanically entangled across large length scales and with large masses. But there is no fundamental evasion of the Heisenberg uncertainty principle here; each individual component is exactly as uncertain as the rules of quantum physics predicts. While it’s important to explore the relationship between quantum entanglement and the different components of the systems, including what happens when you treat both components together as a single system, nothing that’s been demonstrated in this research negates Heisenberg’s most important contribution to physics.”
The papers, published in the journal Science, could help create new generations of ultra-sensitive measuring devices and quantum computers.


Quantum Computing: Understanding the Basics and Its Potential Impact
Quantum computing is an emerging field of technology with the potential to revolutionize the way computing is done. It promises incredible performance boosts, faster and more efficient computing, and even the ability to process information in ways that are impossible right now. But what is quantum computing, and what impact could it have?
What is Quantum Computing?
Quantum computing is a method of computing that takes advantage of the rules of quantum mechanics. It uses qubits instead of classical bits, which enables them to hold much more data than normal binary bits. This gives quantum computers the ability to perform operations at a much faster speed than traditional computers.
The Potential of Quantum Computing
Quantum computers have the potential to revolutionize many industries and fields. Here are some of the potential applications of quantum computing:
- Data Analysis: Quantum computers are capable of sifting through large datasets and discovering patterns that are too complex for traditional computers to uncover.
- Cryptography: Quantum computers can be used to securely encrypt data, making it virtually impossible for hackers to break through.
- Artificial Intelligence: Quantum machines are able to look at data in a truly unique way, making them ideal for advanced AI applications.
The Challenges Ahead
Despite its amazing potential, quantum computing is still in its infancy. The technology is complex and challenging, and a lot of work still needs to be done to perfect it. There are also numerous challenges that need to be addressed, such as security and reliability.
The Future of Quantum Computing
While the challenges ahead of quantum computing may be daunting, its potential is undeniable. It could profoundly change the way we think about computing, making it possible to solve problems that are currently impossible. The future of quantum computing is sure to be an exciting one.
What is quantum computing basics?
Quantum computing is a rapidly-emerging technology that harnesses the laws of quantum mechanics to solve problems too complex for classical computers. Today, IBM Quantum makes real quantum hardware — a tool scientists only began to imagine three decades ago — available to hundreds of thousands of developers. Quantum computing works on the principle of quantum logic. It uses qubits — particles like electrons and photons — instead of the binary digits (bits) used in classical computing. These qubits can exist in multiple states simultaneously and represent both 1s and 0s at the same time. As a result, a single qubit can contain much more information than a classical bit and make calculations faster and more complex.
What is the impact of quantum computing?
With computing power based on the known universe’s power, quantum computers will do the math at a speed of 158,000,000 times faster than conventional computers. They can solve a computation in four minutes that would take today’s computers thousands of years to solve. This fact alone poses a great number of opportunities. The wide range of potential applications include machine learning, big data analysis, artificial intelligence, simulation of organic molecules, and the simulation of complex financial models.
Quantum computing can enable the development of smarter and faster research, faster transportation, the development of the Internet of Things (IoT), and will lead to revolutionary medical breakthroughs. For example, it could enable us to develop new medicines and treatments faster than ever before. Along with the advancement of medical science, quantum computing could help in the development of new materials and substances.
In the world of finance, quantum computing could have a dramatic impact on the ability to optimize markets, portfolios, and transactions. This could lead to the development of smarter trading systems and improved predictive analytics.
Finally, quantum computing could help to safeguard national information and improve cybersecurity. It has been suggested that quantum computers could drastically reduce the security risks posed by hackers because quantum computing could break current encryption algorithms.
What is the potential of quantum computing?
By solving problems with more accuracy and speed than digital computers, quantum computers have the potential to accelerate scientific discovery and innovation, revolutionize financial market modeling and simulations, and empower machine learning and artificial intelligence. It could also create far more secure databases and networks, allowing for encrypted machines that can’t be hacked. In the future, quantum computers have the potential to lead to revolutionary advancements in encryption and computing power that revolutionize the way we interact with technology.
What impact will quantum computing have on humans lives?
Quantum computing has many potential uses, such as quantum engineering, cryptography, machine learning, artificial intelligence, simulations, and optimizations. It could speed up drug discovery and help with medical research by speeding up chemical reactions or protein folding simulations. Quantum computing could also be used for efficient data storage, data security, and quantum communications. Quantum computing could revolutionize the cryptocurrency market and be used for the secure sharing of data. It could also be used to process large amounts of data quickly, which could help with decision making and risk management. Ultimately, quantum computing could help improve our lives in many ways by helping to make data more secure, advancing medical research, and enabling more efficient and powerful calculation.
There are no reviews yet.


SEPTEMBER 8, 2021 — A UTSA researcher is part of a collaboration that has set a world record for innovation in quantum computing. The accomplishment comes from R. Tyler Sutherland, an assistant professor in the College of Sciences’ Department of Physics and Astronomy and the College of Engineering and Integrated Design’s Department of Electrical Engineering, who developed the theory behind the record-setting experiment.
Sutherland and his team set the world record for the most accurate entangling gate ever demonstrated without lasers.
According to Sutherland, an entangling gate takes two qubits (quantum bits) and creates an operation on the secondary qubit that is conditioned on the state of the first qubit.
“For example, if the state of qubit A is 0, an entangling gate doesn’t do anything to qubit B, but if the state of qubit A is 1, then the gate flips the state of qubit B from 0 to 1 or 1 to 0,” he said. “The name comes from the fact that this can generate a quantum mechanical property called ‘entanglement’ between the qubits.”
Sutherland adds that making the entangling gates in your quantum computer “laser-free” enables more cost-effective and easier to use quantum computers. He says the price of an integrated circuit that performs a laser-free gate is negligible compared to the tens of thousands of dollars it costs for a laser that does the same thing.
“Laser-free gate methods do not have the drawbacks of photon scattering, energy, cost and calibration that are typically associated with using lasers,” Sutherland explained. “This alternative gate method matches the accuracy of lasers by instead using microwaves, which are less expensive and easier to calibrate.”
This quantum computing accomplishment is detailed in a paper Sutherland co-authored titled, “High-fidelity laser-free universal control of trapped-ion qubits.” It was published in the scientific journal, Nature, on September 8.
Quantum computers have the potential to solve certain complex problems exponentially faster than classical supercomputers.
One of the most promising uses for quantum computers is to simulate quantum mechanical processes themselves, such as chemical reactions, which could exponentially reduce the experimental trial and error required to solve difficult problems. These computers are being explored in many industries including science, engineering, finance and logistics.
“Broadly speaking, the goal of my research is to increase human control over quantum mechanics,” Sutherland said. “Giving people power over a different part of nature hands them a new toolkit. What they will eventually build with it is uncertain.”
That uncertainty, says Sutherland, is what excites him most.
Sutherland’s research background includes quantum optics, which studies how quantum mechanical systems emit light. He earned his Ph.D. at Purdue University and went on to Lawrence Livermore National Laboratory for his postdoc, where he began working on experimental applications for quantum computers.
He became a tenure-track assistant professor at UTSA last August as part of the university’s Quantum Computation and Quantum Information Cluster Hiring Initiative.
UTSA Today is produced by University Communications and Marketing, the official news source of The University of Texas at San Antonio. Send your feedback to firstname.lastname@example.org. Keep up-to-date on UTSA news by visiting UTSA Today. Connect with UTSA online at Facebook, Twitter, Youtube and Instagram.
Come join us at "Taste of Success" in the Loefller Room to hear about the opportunities that the Department of Physics and Astronomy has to offer with guest speaker Dr. Chris Packham.Loeffler Room (BSB 3.03.02,) Main Camus
Learn to use the simple but powerful features of EndNote, a citation management tool. In this hands-on workshop, participants will learn to setup an EndNote library, save references and PDFs, and automatically create and edit a bibliography.Virtual event
Do you professors require the use of BibTex or LaTex to format your references? This workshop will cover where to get your references in BibTex format, import them into a LaTex editor, and much more.Virtual event
Join us as we raise awareness to the topic of child abuse through Cardboard Kids decoration. We have basic art supplies, feel free to bring extra embellishments. This will be in indoor space next to FreeBirds. Trigger Warning: This event is intended to raise awareness of child abuse, child abuse will be a topic of conversation.Outdoor Learning Environment 1 (OLE,) Student Union, Main Campus
Join the UTSA community in celebrating the life of Dr. Thelma Duffey.Aula Canaria (BV 1.328), Buena Vista Building, Downtown Campus
The proposed annual BME Research Symposium will allow students to present their undergraduate research free of charge, providing them with the opportunity to network and build their professional skills.H-E-B Student Union Ballroom 1 & 2, Main Campus
The UTSA Marches Committee, in partnership with the Cesar E. Chavez Legacy and Education Foundation, invites everyone to the 27th annual Cesar E. Chavez March for Justice. This event is in conjunction with the "Yes We CAN" food donation drive with the San Antonio Food Bank. Guests are encouraged to bring canned food items with them to the march to deposit cans into barrels before the march begins.1310 Guadalupe St, San Antonio, TX 78207
The University of Texas at San Antonio is dedicated to the advancement of knowledge through research and discovery, teaching and learning, community engagement and public service. As an institution of access and excellence, UTSA embraces multicultural traditions and serves as a center for intellectual and creative resources as well as a catalyst for socioeconomic development and the commercialization of intellectual property - for Texas, the nation and the world.
To be a premier public research university, providing access to educational excellence and preparing citizen leaders for the global environment.
We encourage an environment of dialogue and discovery, where integrity, excellence, inclusiveness, respect, collaboration and innovation are fostered.
UTSA is a proud Hispanic Serving Institution (HSI) as designated by the U.S. Department of Education.
The University of Texas at San Antonio, a Hispanic Serving Institution situated in a global city that has been a crossroads of peoples and cultures for centuries, values diversity and inclusion in all aspects of university life. As an institution expressly founded to advance the education of Mexican Americans and other underserved communities, our university is committed to ending generations of discrimination and inequity. UTSA, a premier public research university, fosters academic excellence through a community of dialogue, discovery and innovation that embraces the uniqueness of each voice.


How Does a Dilution Refrigerator Work?
A cryogen-free dilution refrigerator is a closed-loop cooling system that provides cooling to temperatures of millikelvins – colder than outer space. The system is used to cool down samples and devices, which are attached to a metallic flange in the dilution refrigerator. The systems are used for instance in quantum computing, materials science, astrophysics, and fundamental research.
The dilution refrigerator systems can provide temperatures of < 10 millikelvin and can operate without moving parts at the low temperature stages. This is enabled by the dilution unit inside the system, which provides necessary cooling to reach these ultra-low temperatures. The cooling power of the dilution unit comes from the heat of mixing of the mixture of helium-3 (He-3) and helium-4 (He-4) isotopes. This is enabled by the peculiar property of helium, that its two isotopes can remain dissolved down to the lowest temperatures, whereas other fluids tend to separate completely at sufficiently low temperature.
Phase Separation of Helium Isotopes
He-3 and He-4 represent two different fundamental particles. He-3 is a fermion, while He-4 is a boson. Bosons can undergo a phenomenon called Bose-Einstein condensation, where multiple particles can occupy the lowest quantum mechanical energy state. This phenomenon is responsible for the onset of superfluidity of He-4 at 2.17 kelvin under saturated vapor pressure. For fermions, on the other hand, such phenomenon is not possible since only two fermions (with opposite spins) are allowed to occupy same quantum mechanical energy state. The superfluid state in He-3 is thus much more difficult to achieve, and it does not happen in the operational temperature range of the dilution refrigerator. The normal fluid He-3 is also called fermi fluid.
A dilution refrigerator uses the heat of mixing of those two isotopes of helium, He-3 and He-4, to obtain cooling. At temperatures below 0.87 kelvin (exact temperature depends on the He-3 concentration) the He-3– He-4 mixture will separate into two phases: an He-3 rich phase (concentrated phase) and an He-3 poor phase (dilute phase).
Phase diagram of helium-3—helium-4 mixture.
Approaching absolute zero temperature, the concentrated phase becomes pure He-3 while in the dilute He-4 rich phase there remains 6.6% of He-3. The enthalpy of He-3 in the dilute phase is larger than in the concentrated phase. Hence energy is required to move He-3 atoms from the concentrated to the dilute phase. In a dilution refrigerator this energy is taken from a well isolated environment so cooling will occur.
Essentially the cooling provided by the dilution unit is based on the He-3 requiring heat when pumped into the dilute phase, which provides cooling in the environment this happens in.
Operation of the Dilution Unit
In the dilution refrigerator, the isolated environment where the mixing of the isotopes happens is called the Mixing Chamber. That’s where the phase boundary is located, and where the cooling occurs when the He-3 is pumped through the phase boundary. Other essential parts of the dilution unit are the still chamber, the continuous flow heat exchanger (in the form of a spiral), and the step heat exchangers.
In a steady state operation, He-3 comes to the dilution unit pumped with a gas handling system. It enters the dilution unit precooled first by the pulse tube cryocooler down to about 3 kelvin, and through the main flow impedance in the still chamber. From there it proceeds to the continuous flow heat exchanger and then to the step heat exchangers, which cool the He-3 going to the mixing chamber. From the mixing chamber the He-3 goes into the still chamber and in a gas phase is evaporated through a still pumping line, eventually coming back to the start of the process. Below you can see a diagram of the cooling cycle.
Dilution refrigerator cooling cycle. 1. He-3-rich gas phase, 2. Still, 3. Heat exchangers, 4. He-3-poor phase, 5. Mixing Chamber, 6. Phase separation, and 7. He-3-rich phase.
The efficiency of the dilution refrigerator is determined by the efficiency of the heat-exchangers. The incoming He-3 should be cooled by the outgoing He-3 as much as possible.
The available cooling power is determined by the circulation rate of He-3. The larger the flow, the larger the cooling power, provided that the heat-exchangers are capable of handling the increased flow rate.
The temperature of the still and mixing chamber plate are controlled by heaters. The mixing chamber has a heater, which is there for diagnostics purposes; it can be used to characterize unit behaviour under various heat loads, i.e., simulate an installed experiment. The still heater on the other hand is essential to the unit operation. Without heating, the vapor pressure in the still chamber becomes so small, that pumps cannot effectively circulate He-3, resulting in reduced cooling power. Hence, heat must be applied to the still to increase evaporation. As He-3 has larger vapor pressure than He-4, this process distils He-3 out of the mixture (the He-3 concentration in the gas phase is ~90%)
After the He-3 gas evaporates from the still, it is pumped through a gas handling system (GHS), in which it is purified and then allowed back into the condensing line.
Dilution unit. 1. Still, 2. Continuous flow heat exchangers, 3. Step heat exchangers, and 4. Mixing chamber.
The entire dilution refrigerator consists of the different temperature stages, with the dilution unit located in the lowest stages. The stages are easily recognizable as they are made of large metallic plates. The stages are separated by non-conductive supports and heat switches, whose conductivity can be controlled. Using them the stages can be thermally connected or disconnected. The dilution unit is attached to three of these metallic plates. The still chamber of the dilution unit sits on top of the still flange, under that and after the continuous flow heat exchanger there is the cold plate, and the mixing chamber is located on top of the mixing chamber flange. Finally, below that there is the experimental space enabling measurements in millikelvin temperatures. All these stages will have temperature sensors to provide the user information about the temperatures at different stages.
Cooling With a Push of a Button
For the user of a dilution refrigerator all this cooling power is provided with a push of a button providing ease of use, with no need to understand all the mechanics proving this cooling. But for those that are curious, you now know that the dilution unit is the heart of the dilution refrigerator and enables it to provide the lowest temperatures for research and applications.
There are however numerous other components to the dilution refrigerator measurement system. Somehow all the helium in the system has to move around it and be precooled to the temperatures required for the dilution unit operations. We must also protect all of this from the outside environment to keep everything running efficiently. To learn about all that, read our blog on the components of the dilution refrigerator measurement system.


The general public might think of the 21st century as an era of revolutionary technological platforms, such as smartphones or social media. But for many scientists, this century is the era of another type of platform: two-dimensional materials, and their unexpected secrets.
These 2-D materials can be prepared in crystalline sheets as thin as a single monolayer, only one or a few atoms thick. Within a monolayer, electrons are restricted in how they can move: Like pieces on a board game, they can move front to back, side to side or diagonally — but not up or down. This constraint makes monolayers functionally two-dimensional.
The 2-D realm exposes properties predicted by quantum mechanics — the probability-wave-based rules that underlie the behavior of all matter. Since graphene — the first monolayer — debuted in 2004, scientists have isolated many other 2-D materials and shown that they harbor unique physical and chemical properties that could revolutionize computing and telecommunications, among other fields.
For a team led by scientists at the University of Washington, the 2-D form of one metallic compound — tungsten ditelluride, or WTe2 — is a bevy of quantum revelations. In a paper published online July 23 in the journal Nature, researchers report their latest discovery about WTe2: Its 2-D form can undergo “ferroelectric switching.” They found that when two monolayers are combined, the resulting “bilayer” develops a spontaneous electrical polarization. This polarization can be flipped between two opposite states by an applied electric field.
“Finding ferroelectric switching in this 2-D material was a complete surprise,” said senior author David Cobden, a UW professor of physics. “We weren’t looking for it, but we saw odd behavior, and after making a hypothesis about its nature we designed some experiments that confirmed it nicely.”
Materials with ferroelectric properties can have applications in memory storage, capacitors, RFID card technologies and even medical sensors.
“Think of ferroelectrics as nature’s switch,” said Cobden. “The polarized state of the ferroelectric material means that you have an uneven distribution of charges within the material — and when the ferroelectric switching occurs, the charges move collectively, rather as they would in an artificial electronic switch based on transistors.”
The UW team created WTe2 monolayers from its the 3-D crystalline form, which was grown by co-authors Jiaqiang Yan at Oak Ridge National Laboratory and Zhiying Zhao at the University of Tennessee, Knoxville. Then the UW team, working in an oxygen-free isolation box to prevent WTe2 from degrading, used Scotch Tape to exfoliate thin sheets of WTe2 from the crystal — a technique widely used to isolate graphene and other 2-D materials. With these sheets isolated, they could measure their physical and chemical properties, which led to the discovery of the ferroelectric characteristics.
WTe2 is the first exfoliated 2-D material known to undergo ferroelectric switching. Before this discovery, scientists had only seen ferroelectric switching in electrical insulators. But WTe2 isn’t an electrical insulator; it is actually a metal, albeit not a very good one. WTe2 also maintains the ferroelectric switching at room temperature, and its switching is reliable and doesn’t degrade over time, unlike many conventional 3-D ferroelectric materials, according to Cobden. These characteristics may make WTe2 a promising material for smaller, more robust technological applications than other ferroelectric compounds.
“The unique combination of physical characteristics we saw in WTe2 is a reminder that all sorts of new phenomena can be observed in 2-D materials,” said Cobden.
Ferroelectric switching is the second major discovery Cobden and his team have made about monolayer WTe2. In a 2017 paper in Nature Physics, the team reported that this material is also a “topological insulator,” the first 2-D material with this exotic property.
In a topological insulator, the electrons’ wave functions — mathematical summaries of their quantum mechanical states — have a kind of built-in twist. Thanks to the difficulty of removing this twist, topological insulators could have applications in quantum computing — a field that seeks to exploit the quantum-mechanical properties of electrons, atoms or crystals to generate computing power that is exponentially faster than today’s technology. The UW team’s discovery also stemmed from theories developed by David J. Thouless, a UW professor emeritus of physics who shared the 2016 Nobel Prize in Physics in part for his work on topology in the 2-D realm.
Cobden and his colleagues plan to keep exploring monolayer WTe2 to see what else they can learn.
“Everything we have measured so far about WTe2 has some surprise in it,” said Cobden. “It’s exciting to think what we might find next.”


Secrets of the superfast computers of tomorrow
Image 1 of 14
The thorniest problems, solved in days
Qubits allow multiple states to be simultaneously stored. The process, known as superposition, gives quantum computers (envisioned in this concept art) exponentially faster processing speeds.
Problems that would take traditional computers millions of years to solve could instead take days.
But they can't take the heat
One of the challenges, however, is building a chip that can support multiple qubits. The problem: Quantum computers need to operate at near-absolute zero temperatures.
Right now, D-Wave is the only quantum computing company that has managed to manufacture a processor with more than 1,000 qubits, a milestone that paves the way for further advancements in the field.
Can we beat China?
We may be years away from fully harnessing the power of quantum computers, but that hasn’t stopped the U.S. government from pursuing the next-best thing, a supercomputer that will be more than five times faster than China’s Tianhe-2, shown here.
Get to know petaflops
Contracted by the US Department of Energy, the supercomputer named Aurora will be able to reach a peak performance of 180 petaflops, or 180 quadrillion operations a second.
Speed beyond reckoning
Need help visualizing a quadrillion? An average American employee would have to work full-time for 250 million years to earn a quadrillion pennies.
Aurora's potential: Pick a technology
The Aurora will be primarily dedicated to scientific projects. Other potential uses: designing better batteries and solar panels, or improving transportation systems and wind turbines.
The Aurora will be built by Intel and Cray Inc., and will cost $200 million to build. It’s expected to become operational by 2018.
Harnessing the most powerful computer
Most supercomputers are built to take on multiple scientific projects, but the Blue Brain Project has just one simple goal: to reverse-engineer the human brain and create a virtual brain in a supercomputer.
Neuron by neuron
Started in 2005 by the u00c9cole polytechnique fu00e9du00e9rale de Lausanne in Switzerland, the objective of the Blue Brain Project is to simulate each neuron of the human brain to better understand the brain and the development of neurological diseases.
Here, Blue Brain scientist Ying Shi eyeballs a 3D animation of one such brain neuron.
$1 billion brain
Considering there are around 100 billion neurons in an average human brain, the scope of the simulation is staggering. Perhaps that’s why the project is starting smaller, with rat brain tissue, shown here undergoing a Blue Brain experiment.
Thanks to a $1.3 billion grant from the European Commission in 2013, the project is well underway, with an estimated completion date in 2023.
With so many supercomputers in operation worldwide (including Japan’s K Computer, shown here), it’s no wonder that the U.S. government is trying to research the next best thing.
Partnering with IBM, Raytheon, and Northrop Grumman, IARPA, the super-secretive arm of the U.S. Department of Defense’s DARPA project, is doing just that.
Make way for the exaflop
Known as Cryogenic Computing Complexity, or C3, the project is expected to pave the way for exascale computing, which would allow computers to perform 1,000 petaflops, or 1 exaflop, a second.
Unlike most modern supercomputers (like this petaflop computer in Germany), the C3 would involve superconductors that don’t need heavy-duty cooling solutions.
Stone cold amazing
Further, C3 would develop cryogenic memory, which as the name implies, would serve as a supercooled memory complement to the superconducted processors.
If successful, C3 would seem light years ahead of today’s most amazing computers, such as NASA’s Pleiades.
That said, it’s currently unclear when the first C3 supercomputer will see the light of day.
Supercomputers at home
What if, instead of being limited to scientists, researchers, and analysts, everyone had access to a supercomputer?
That’s the thinking behind supercomputer.io, an online collaborative that crowdsources computing power from thousands of users who own a Parallella computer, a multi-core bare-bones computer sold by Adapteva.
Processor pipe dreams
It’s expected that supercomputer.io will grow its userbase, unlocking its potential to use tens of thousands and even a million cores, allowing it to tackle more complex problems.
Until that day, supercomputers such as Switzerland’s Piz Daint, with its 36,096 cores (shown here), will just have to do.


Every day, there seems to be a new advancement in computing–whether it’s OpenAI releasing ChatGPT AI, or Google announcing a breakthrough in quantum computing. Some researchers think that traditional computing is reaching its limits, despite all these advances.
In order to create the next generation of technology, some scientists are getting inspiration from the world’s most powerful computer: the human brain. Biocomputing is a field that uses biological molecules such as DNA and cells to create hardware. The idea is that if we’re able to merge brain organoids, or clumps of neurons in a petri dish, with computing systems then we might be able to create computers with the operational power of the human mind.
The concept isn’t exactly new. We’ve seen biocomputers in movies, books, and TV shows like Dune and The Terminator. There have also been limited instances of it in real life. In October 2022, a team of scientists were even able to demonstrate that a group of brain cells in a petri dish could “play” the video game Pong. DishBrain was a system that connected to a cluster of neurons. To move the paddle to hit the ball, the cells would send electrical signals to the computer to tell it what to do.
Over time, the neurons were actually able to improve their Pong game–reducing the amount of times they missed the ball and increasing the amount of times they did. They were capable of adapting to the new environment and setting goals. While they might have mad gaming skills, a fully operational biocomputer still remains a bit of a white whale for biotechnologists.
“Since the beginning of the computer era, engineering has aimed to emulate brain-like functionality, most obviously by striving for artificial intelligence,” Thomas Hartung, a professor of environmental health sciences at Johns Hopkins, told The Daily Beast. “Still, we are far away from achieving brain functionality [in a computer.]”
Advances in brain organoids have shown that they’re able to replicate certain aspects of memory and even cognition while in a petri dish. Hartung leads a Johns Hopkins team that is creating the field of organoid Intelligence (OI) which describes developments in biocomputer technology and the systems involved. The group published a paper of their proposal in the journal Frontiers in Science on Feb. 28.
The team believes that research into biocomputing would have a number of benefits outside of creating more advanced and powerful computers. It would also be more efficient in terms of energy and better for the environment. Frontier, one of the world’s most powerful supercomputers, was able to produce the computational capacity of a single human brain just last year, according to Hartung. However, it requires a “million times more energy” than our minds–not to mention $600 million.
“The hope is that some of the remarkable functionalities of the human brain can be realized in OI such as its ability to make fast decisions based on incomplete and contradictory information (intuitive thinking), the continuous learning, and the data- and energy-efficiency,” Hartung explained.
Additionally, Hartung claimed that the field of OI could also lead to the development of new treatments for neurological disorders like dementia or Alzheimer’s. The development of biocomputers requires research into the “biology of learning, memory, and other cognitive functions.” This will allow scientists to use brain organoids to potentially test for new drugs and treatments for cognitive decline.
There are many ethical issues to be aware of when dealing with mini-brains. Issues surrounding potential sentience or self-awareness with biocomputers need to be addressed–which brings into question whether or not something like this should be pursued at all.
What does it mean if the computer you’re using is essentially a human inside of a machine? Can it experience “pain?” What do we even consider sentient when it comes to computers anyway? What happens when a biocomputer crosses this line?
To their credit, the team is incorporating ethicists into their OI discussions and “agreed on a concept of embedded ethics where they actually follow developments and observe the actual work in the laboratory,” Hartung said. However, ethical questions surrounding biocomputing are likely to remain as long as human brain cells continue being used.
A fully functional biocomputer remains a distant reality. Hartung believes that it could take decades before OI is powerful enough to have the computational power of a mouse’s brain. However, the research to actually create a biocomputer will go a long way in not only creating the next generation of computers, but also potentially finding new treatments for some of the most destructive neurodegenerative conditions out there.
And you don’t need the smartest brain to see why that’s good.
The post How Human Brain Cells Might Someday Power Computers appeared first on The Daily Beast.


Quantum Computing involves the use of several quantum phenomena to perform computations. One of these is entanglement. These phenomena help speed up exponentially the computational power, thus bringing computing to the next level as quantum computers operate at much higher speeds than classical computers. It also allows them to use less energy in performing the same operations as a classical one.
Decoherence and quantum computing
Quantum computers are very powerful, but they are also very fragile. When qubits interact with their environment, they decay and ultimately disappear in a process called decoherence.
Decoherence is caused by a range of factors, including light, heat, sound, vibration, radiation, and even the act of measuring a qubit itself.
While supercooled fridges and vacuum chambers are used to shield qubits from the outside world, errors still creep into quantum calculations. Technology is not yet sufficiently advanced to create a stable quantum computer that is broadly useful.
Why does quantum computing matter?
The need for knowledge has always engulfed humans and is the major driver of technological evolutions. From what started as an abacus and turned into high-end calculators for everyday use, computers have seen a similar advancement. Within three decades, computing powers changed from a mere five thousand addition problems (ENIAC) to millions of complex problems in a matter of seconds.
This exponential advancement has not hindered the progress that humans still dream of achieving. Technological changes have always occurred whenever there has been a problem to solve. The work of decades upon decades in different technological areas has left little room for improvements. However, whenever existing technology was unable to solve the tasks at hand, humans have tried to resolve the issue with further advancement.
One similar case has been that of Quantum Computing. When complexities ensued and classical computers could not answer the underlying questions, quantum computers were invented. Hence, a new era of advancement followed.
Understanding quantum computing
Modern computers encode information in bits that have a binary value. That is, the information can only take a value of 1 or 0.
Quantum computers, on the other hand, utilize subatomic particles called quantum bits (qubits). Qubits possess some strange quantum properties. Connected qubits provide a significant increase in processing power when compared to the equivalent number of bits in a modern computer.
The quantum properties responsible for this increased performance are:
- Superposition – defined as the ability to exist in multiple states. Qubits can represent numerous possible combinations of 1 and 0 simultaneously. This enables quantum computers to rapidly assess a vast number of potential outcomes. Once a result has been calculated, the quantum state of qubits reverts to a binary state of either 1 or 0.
- Entanglement. Qubits are said to be entangled when two members of a pair exist in a single quantum state. In other words, changing the state of one qubit will instantaneously change the state of the other. Scientists do not understand how or why entanglement occurs but adding entangled qubits to a quantum computer produces an exponential increase in computational power.
How does quantum computing work?
As the name suggests, Quantum Computing involves the use of several quantum phenomena to perform computations. One of these is entanglement. Quantum entanglement is basically a phenomenon that occurs when a group or a pair of particles interact or are in the same proximity but their quantum state cannot be determined independently of each other.
Similarly, another phenomenon that is part of Quantum Computing is superposition. Superposition states that any two quantum states can be added or “superposed”. The result will be another quantum state. In the same way, this also entails that every quantum state is a sum of other quantum states which can be two or more in number. Quantum Computing uses these phenomena to perform faster computations than classical computers such as integer factorization.
It is widely argued that whichever problems that quantum computers solve, can also be solved by classical computers. Alternatively, whichever problems can be solved by classical computers as well. The difference that exists between the two is the time that both take while solving the problems. This advantage of quantum computers over classical computers is known as “quantum supremacy”. Just like classical computers store information in the form of bits (0 or 1), quantum computers use what are known as “qubits”.
As mentioned before, using phenomena like superposition and entanglement quantum computers are able to allow subatomic participles in more than one state. This means that at the same time it could be a 1 or a 0. This makes quantum computers operate at much higher speeds than classical computers. It also allows them to use less energy in performing the same operations as a classical one.
Commercial applications for quantum computing
Quantum Computing has a wide array of applications, which makes it one of the most exciting technologies to look forward to. Within the healthcare industry, it cannot only be used for research purposes but diagnostics and treatment as well. Since quantum computers have high processing power, it will enable researchers to use them in order to simulate interactions between different proteins of the human genome and drugs.
This will allow them to evaluate drugs based on their interactions and can lead to pharmacological advancements. In diagnostics, MRI machines can be made to operate at higher levels and provide greater detail which will help the doctors in identifying medical issues. Similarly, treatments like radiotherapy can be further enhanced due to the use of quantum computing as it will be able to withstand complex simulations and provide answers in a timely manner.
In the field of Finance, quantum computing can help in detecting fraud based on pattern recognition. Coupled with machine learning, neural networks can be trained timely and thereby improving the detection rate immensely. From a Marketing perspective, quantum computing can be used to process and analyze large amounts of data which can be used to put forward targeted advertisements at potential customers based on their behavior.
The same can be done through classical computers, but quantum computing certainly has an edge in providing better and timely service due to the data being in large amounts. Optimization problems, which are encountered by companies like delivery services or arranging flight schedules, can be solved using quantum computers. It has uses in almost all avenues, whether they are public projects or advancements in data handling. What would normally take unimaginable amounts of time can be solved through the use of quantum computers.
Major advantages of quantum computing
The major advantage that quantum computers hold is that they are equipped to find optimal solutions to problems that have infinitely many variables. Due to their high processing power, quantum computers are able to run millions of simulations to test whatever theories that users might have. This gives it an ultimate advantage over other systems.
Quantum computers at extremely cold temperatures. The temperatures required are near absolute zero. To achieve such a cold temperature, the chip is required to be cooled down. This is achieved through liquified helium, which makes the chip very cold. To achieve superconductivity, such low temperatures are essential for quantum computing.
Research is being conducted to make quantum computing possible at higher temperatures, but no such significant improvement is expected in the near future.
Scientists are developers are constantly in the run to make quantum computing possible given the large number of applications that it entails. Machine learning will benefit the most when stability is achieved in terms of quantum computations. Technology giants like Google and IBM are in the constant run to achieve quantum supremacy, with each taking steps to ensure the world witnesses a stable quantum computer in the next few years.
What’s the major drawback (for now) of quantum computing?
One of the issues that quantum computers encounter is any disturbance in the computer’s surroundings. Since they are very fragile, vibrations in the surroundings can impact the atoms, and decoherence will be caused. Despite their high demands, quantum computers will actually reduce the power consumption to operate. This is achieved through a process known as “quantum tunneling.” The possibilities are endless, and researchers are in a rush to make it happen.
Other potential applications for quantum computing
The potential applications for quantum computing are understandably vast. But in the short term, some of the most promising applications include:
- Simulating the behavior of matter at the molecular level. Volkswagen and Daimler AG are using quantum computers to simulate the chemical composition of electric-vehicle batteries. The auto-makers hope that these simulations will highlight new ways of making battery technology more efficient. Pharmaceutical companies are using similar chemical simulations to assess compounds that could be used in new drugs.
- Optimization. An obvious application of quantum computing is any scenario where a large amount of data must be analyzed in a timely fashion. Airbus is using the technology to help determine the most fuel-efficient ascent and descent paths for their range of aircraft. Volkswagen is also using quantum computing to calculate routes that avoid congestion for taxis in large cities.
- Quantum computing uses elements of quantum mechanics to create high-performance computers that analyze large amounts of data rapidly.
- Quantum computing is based on qubits and the two quantum properties of superposition and entanglement. Qubits offer significant benefits over traditional binary computers because they can exist in multiple states simultaneously.
- Quantum computing is still in its infancy because qubits tend to decay to a non-quantum state when exposed to disturbances. Nevertheless, they are currently being used in the transport and pharmaceutical industries to drive innovation and performance.
Connected Business Frameworks And Analyses
Stability AI Ecosystem


Internet security could soon have a new enemy: quantum computers. Such computers will be able to break existing encryption algorithms, removing protection for data exchanged over the Internet. Those who build quantum computers will make a lot of money.
These statements make appealing headlines. However, we must exercise caution when thinking about real-world implications of quantum computing. In reality, a general-purpose quantum computer doesn’t exist yet. The day it does, it will be fast, but pretty bad at solving cryptographic puzzles. Some companies – like European IT services corporation Atos – are already selling quantum software, without ever having built a quantum computer. And the true business case for using this technology should interest smart-city visionaries more than those who are concerned with Internet privacy.
Quantum is not for code breaking
Contemporary semiconductors process information using bits, that is, units that can take either a state of 0 or the state of 1. Quantum computing relies on qubits (aka quantum bits). A qubit can simultaneously take a state of 1 and 0. Hence, two qubits can represent four states, four qubits 16 states and so forth. In addition, qubits are “entangled” because they can interact with one another to arrive at a solution.
While the current semiconductors enable exact calculations (2+2=4), quantum computing is based on probabilities. In addition, most current qubit technologies require an extremely low temperature to operate. Higher temperatures decrease qubits’ stability, ultimately increasing computational noise. When you compute 2+2, the quantum computer will return several results, with 4 ideally having the highest probability. Yet, given the noise, when someone computes 2+2 hundreds of times, it might be that in some of the iterations, 4 isn’t the result with the highest probability. While companies invest a lot of money to reduce the noise in quantum calculations, it is likely to be there for a long time.
These difficulties could well make quantum processors unsuitable for common encryption problems. Computers rely on precise calculations when encrypting or decrypting files. A recipient would not be able to decrypt an encrypted message using a quantum processor. Such a processor would only be able to approximately apply encryption keys. Consequently, it might be unable to break encryption behind current Internet protocols.
Develop quantum software before hardware
As you can imagine, there is no single standard for building a quantum computer. It is as if we were in the pre-ENIAC days when no one knew how to build a transistor, not to mention a CPU. Companies like IBM or Microsoft are investing a lot of money to build quantum hardware. This is an expensive and highly uncertain task.
Atos, under the leadership of its CEO Thierry Breton, has chosen a different path. It has developed the Atos Quantum Learning Machine (Atos QLM) which allows programmers to write software without waiting for a general-purpose quantum computer to be built. The QLM can do that because it simulates the laws of physics that govern quantum computing. A similar technique is used to simulate behaviours of physical projects that don’t yet exist, such as airplanes. For example, a programmer can state that she wants to simulate interactions with a 16-qubit quantum computer, and the platform will behave accordingly. As of July 2018, the QLM was capable of simulating up to 41 qubits.
As more and more companies use this platform, they are likely to converge on a common approach to program quantum computers and may also agree on what quantum hardware should look like. It would be like giving ENIAC’s creators in 1940s a platform for writing programs on an Intel processor in 1970s. This, in turn, would allow engineers to create a better ENIAC in anticipation of Intel’s architecture. Hence, software will drive the hardware with Atos leading the way into the future. According to the Atos executives I interviewed, their QLM sells really well in the United States. This makes them proud to be part of a European company that can compete on an equal (or better) footing with much larger American players. It also puts Atos at the core of the emerging ecosystem around quantum computing, as other participants develop technologies that would be compatible with QLM.
Quantum in smart cities
Despite its challenges, quantum computing is best suited for cases that involve massive data processing, but don’t require 100 percent precision in computations. Future smart cities represent a context in which such problems abound. Imagine London or Paris full of driverless cars. The artificial intelligence algorithms, sitting under the hood of every smart car, would solve the local problems. They would navigate the streets by constantly scanning the car’s environment to determine the best tactic, for instance, should the car stop or accelerate at the nearby intersection. Yet, such local decisions might not be optimal on a larger scale. Thus, the city might want to have a quantum computer to optimise the city-wide traffic flows. The system could give different suggestions to different cars to shorten their travel time. Even if a given forecast – e.g. the next five cars should detour via Street A to unclog Street B – is only 98 percent accurate, it would still be good enough on average. Everyone would have a better chance to arrive in time for dinner. Other possible uses of quantum computing include the optimisation of electrical grids: This is another problem that requires massive computational power, but can tolerate small errors.
Working with quantum computers is a little like being in Alice’s Wonderland. These computers will be powerful, yet imprecise; a general-purpose machine is not built, yet we can write software for it. They will not be privacy’s enemies, but the friends of complex problems.
Andrew Shipilov is a Professor of Strategy and Akzo Nobel Fellow at INSEAD. He is a programme director for Blue Ocean Strategy, an Executive Education programme. He is also a co-author of Network Advantage: How to Unlock Value from Your Alliances and Partnerships.
Leave a Comment
No comments yet.