Quantum physics deals with the realm of the very small, and most of us never expect to see the weird world it describes. But could we? Recently, scientist Geraldo Barbosa of Northwestern University designed an experiment to answer that question.
The quantum effect Barbosa is hoping to see is called quantum entanglement, in which two or more particles can become "entangled" so that even after they are separated in space, when an action is performed on one particle, the other particle responds immediately.
A common experiment illustrating entanglement is to fire a laser at a special type of crystal. Occasionally a photon particle from the laser "splits" into two. The energy and momentum of the two new photons each add up to the value of the one originally fired.
These two "daughter" photons are entangled — if you look at the state of one photon, you know the state of the other, instantly. Einstein described this eerie connection as "spooky action at a distance."
Next, the physicists change the form of the laser beam in the experiment to create an image. They have found that the image isn't visible unless two detectors are able to "see" the photons at the same time.
While these physics experiments rely on detectors to "see" the photons and the resulting images, Barbosa foresees setting up an experiment in which a person's retinas would act as the detectors. [Stunning Photos of the Very Small]
Spooky action in the lab
The entangled photons have opposite polarization states: in other words, their waves are oriented differently. (On a quantum level, particles can behave like waves, and waves like particles.)
In these experiments when only one photon is detected, it could be in any polarization state and it can hit the detector at any time. That means scientists can't tell whether the photon hitting their detector is from the entangled duo. Without that knowledge, a person can't reconstruct the image these photons are meant to create.
But when both entangled photons are detected, you can figure out the photon's polarization state. Knowing one, you know both, and can recreate the image. The "spooky" part is that by observing either one of the photons you've eliminated all the other possibilities — both observed photons must have the polarization states you see. But how does the entangled photon "know" what state to be in? Relativity says that you can't have information travel faster than light. Observing entangled photons, though "forces" them into a certain state at the same time. [10 Effects of Faster-Than-Light Discovery]
Essentially, the information in both photons is added to recreate the original image. This experiment has been done many times.
But what would happen if the two detectors were human retinas? Would a person see the higher-order image or just the classical one, the flash of light?
Ordinarily, we see things by perceiving the intensity of the light in several wavelengths. Mixing various wavelengths makes up all the various colors and saturations we perceive.
This situation would be different — if brains could see quantum effects like entangled photons, one would expect a different image when looking with one eye than with both. This is a deeper question than it may seem, because if people can see such images, it means our macroscopic brains can pick up subtle, microscopic quantum effects.
Next step in quantum vision
Barbosa said there are still difficulties with setting up such an experiment. One problem is the signal-to-noise ratio in human neurons. We can't perceive individual photons even though they hit our retinas, as it takes a certain number of photons hitting our eyes for our brains to interpret the signal as, for example, a flash of light.
In his paper, which is posted on the physics pre-print website arXiv, Barbosa notes that it is far from clear that one could generate enough photons to trigger a response from the human retina — at least seven photons are necessary to do that, and they would all have to be entangled.
Robert Boyd, professor of optics at the University of Rochester, said he doesn't see anything in principle wrong with the idea. "Even here, there are two possibilities," Boyd wrote in an email to LiveScience. "One is that the human brain simply does not work in the manner that Barbosa proposes. The other is that it does, but that the effect is so weak as to be unobservable."
Barbosa, meanwhile, said he has been thinking about this for a while —he did some of the first experiments with quantum images in his lab in 1994. And he sketches out some of the equipment that would be needed to make the experiment work, such as special goggles to get the photons to the right part of the retina.
"This would only indicate that the complex neural system is able to process quantum signals —an amazing feature," Barbosa wrote.
Copyright 2012 LiveScience, a TechMediaNetwork company. All rights reserved. This material may not be published, broadcast, rewritten or redistributed.


Computers consist of a processing component and a memory component. In the most basic sense, processors perform computations and memory stores data.
For simple computations, a single processor may do the job. For more complex operations, however, multiple processors are often the only way to solve a problem. Many applications in the public and private sector require massive computational resources, such as real-time weather forecasting, aerospace and biomedical engineering, nuclear fusion research and nuclear stockpile management. Since these applications exceed the capacity of a single server, computer engineers have devised high-performance computing platforms that can deliver substantially more processing power. The most powerful computer systems in use today leverage thousands of linked processors to perform computations quickly by sharing the workload among multiple processors.
There are two general models for managing and coordinating large numbers of processors. One is typified by supercomputers. These are large, expensive systems—usually housed in a single room—in which multiple processors are connected by a fast local network. The other is distributed computing. These are systems in which processors are not necessarily located in close proximity to one another—and can even be housed on different continents—but which are connected via the Internet or other networks.
Advantages and Disadvantages of Each Model
The advantage of supercomputers is that since data can move between processors rapidly, all of the processors can work together on the same tasks. Supercomputers are suited for highly-complex, real-time applications and simulations. However, supercomputers are very expensive to build and maintain, as they consist of a large array of top-of-the-line processors, fast memory, custom hardware, and expensive cooling systems. They also do not scale well, since their complexity makes it difficult to easily add more processors to such a precisely designed and finely tuned system.
By contrast, the advantage of distributed systems is that relative to supercomputers they are much less expensive. Many distributed systems make use of cheap, off-the-shelf computers for processors and memory, which only require minimal cooling costs. In addition, they are simpler to scale, as adding an additional processor to the system often consists of little more than connecting it to the network. However, unlike supercomputers, which send data short distances via sophisticated and highly optimized connections, distributed systems must move data from processor to processor over slower networks making them unsuitable for many real-time applications.
Weather forecasting is a prototypical supercomputing problem, in part because of how much data it takes to produce a weather forecast that is accurate by contemporary standards. Weather simulations take in massive quantities of data on temperature, wind, humidity, pressure, solar radiation, terrain, and numerous other environmental factors, and must account for global as well as local changes in these variables. Processing this data on a distributed system would mean repeatedly transferring data over relatively slow networks thereby seriously limit forecasting speeds. Since changes in weather occur continuously, having to wait for data to move around the system makes for forecasts that are already out of date as soon as they are produced. Other examples of supercomputing applications include nuclear stockpile management and large-scale physics simulations such as those involved in aerospace engineering.
In contrast, distributed systems are most useful for problems that are not as sensitive to latency. For example, when NASA’s Jet Propulsion Laboratory (JPL) needed to process high volumes of image data collected by its Mars rovers, a computer cluster hosted on the Amazon Cloud was a natural fit. Such tasks are not substantially hindered by small delays in individual computations, so distributed systems offered the most pragmatic solution. Other distributed computing applications include large-scale records management and text mining.
The Road Ahead
Since the emergence of supercomputers in the 1960s, supercomputer performance has often been measured in floating point operations per second (FLOPS). The CDC 6600, a popular early supercomputer, reached a peak processing speed of 500 kilo-FLOPS in the mid-1960s. To put this in perspective, the processor in an iPhone 5S is nearly 250,000 times faster than the CDC 6600. Since the 1960s, the capabilities of supercomputers have grown tremendously. In 2013, the world’s fastest supercomputer, China’s Tianhe-2, could operate at a peak speed of nearly 34 peta-FLOPS, a 70-billionfold speed increase
Meanwhile, the Amazon cloud, one of the world’s fastest distributed systems, achieved a speed of 1.2 peta-FLOPS for the first time in 2013. While this cannot compete with supercomputers like the Tianhe-2, distributed systems can typically be built much more cheaply than supercomputers. A 2013 HP study found that the hourly cost of renting a processor on a dedicated supercomputer was approximately 2-3 times as great as on a comparable distributed cloud-based system.
Does the relative low cost of distributed computing mean the government should stop investing in supercomputers? Absolutely not. Supercomputers provide a distinct and irreplaceable set of capabilities and will continue to be of critical importance to national priorities for years to come to address problems such as cancer research, macroeconomic modeling, and natural disaster forecasting.
The federal government should continue to fund research for both supercomputing and distributed computing. So far, we are moving in the right direction. The 2014 National Defense Authorization Act directs the Department of Energy to develop supercomputers capable of exa-FLOPS speeds, also known as “exascale” supercomputers, within 10 years, and Obama administration has made distributed computing a key part of its “big data strategy.”
But there is more that could be done. If the federal government wants to maximize the value of its investments in high-performance computing, it will need to reduce barriers to using these technologies. This means it should continue to ensure that high-speed networking infrastructure is available to scientists at a broad range of locations and build tools that allow researchers who lack expertise in supercomputing to leverage high-performance systems. In addition, the world of high-performance computing is evolving quickly and federally-funded research should continue to support investments in next-generation computing technology such as quantum computing and molecular computing.
Photo: Flickr user Sam Churchill


Quantum computers promise to be a revolutionary technology because their elementary building blocks, qubits, can hold more information than the binary, 0-or-1 bits of classical computers. But to harness this capability, hardware must be developed that can access, measure and manipulate individual quantum states.
Researchers at the University of Pennsylvania’s School of Engineering and Applied Science have now demonstrated a new hardware platform based on isolated electron spins in a two-dimensional material. The electrons are trapped by defects in sheets of hexagonal boron nitride, a one-atom-thick semiconductor material, and the researchers were able to optically detect the system’s quantum states.
Fellow Bassett Lab members David Hopper and Raj Patel, along with Marcus Doherty of the Australian National University, also contributed to the study.
There are number of potential architectures for building quantum technology. One promising system involves electron spins in diamonds: these spins are also trapped at defects in diamond’s regular crystalline pattern where carbon atoms are missing or replaced by other elements. The defects act like isolated atoms or molecules, and they interact with light in a way that enables their spin to be measured and used as a qubit.
These systems are attractive for quantum technology because they can operate at room temperatures, unlike other prototypes based on ultra-cold superconductors or ions trapped in vacuum, but working with bulk diamond presents its own challenges.
“One disadvantage of using spins in 3D materials is that we can’t control exactly where they are relative to the surface” Bassett says. “Having that level of atomic scale control is one reason to work in 2D. Maybe you want to place one spin here and one spin there and have them talk them to each other. Or if you want to have a spin in a layer of one material and plop a 2D magnet layer on top and have them interact. When the spins are confined to a single atomic plane, you enable a host of new functionalities.”
With nanotechnological advances producing an expanding library of 2D materials to choose from, Bassett and his colleagues sought the one that would be most like a flat analog of bulk diamond.
“You might think the analog would be graphene, which is just a honeycomb lattice of carbon atoms, but here we care more about the electronic properties of the crystal than what type of atoms it’s made of,” says Exarhos, who is now an assistant professor of Physics at Lafayette University. “Graphene behaves like a metal, whereas diamond is a wide-bandgap semiconductor and thus acts like an insulator. Hexagonal boron nitride, on the other hand, has the same honeycomb structure as graphene, but, like diamond, it is also a wide-bandgap semiconductor and is already widely used as a dielectric layer in 2D electronics.”
With hexagonal boron nitride, or h-BN, widely available and well characterized, Bassett and his colleagues focused on one of its less well-understood aspects: defects in its honeycomb lattice that can emit light.
That the average piece of h-BN contains defects that emit light had previously been known. Bassett’s group is the first to show that, for some of those defects, the intensity of the emitted light changes in response to a magnetic field.
“We shine light of one color on the material and we get photons of another color back,” Bassett says. “The magnet controls the spin and the spin controls the number of photons that the defects in the h-BN emit. That’s a signal that you can potentially use as a qubit.”
Beyond computation, having the building block of a quantum machine’s qubits on a 2D surface enables other potential applications that depend on proximity.
“Quantum systems are super sensitive to their environments, which is why they’re so hard to isolate and control,” Bassett says. “But the flip side is that you can use that sensitivity to make new types of sensors. In principle, these little spins can be miniature nuclear magnetic resonance detectors, like the kind used in MRIs, but with the ability to operate on a single molecule.
Nuclear magnetic resonance is currently used to learn about molecular structure, but it requires millions or billions of the target molecule to be assembled into a crystal. In contrast, 2D quantum sensors could measure the structure and internal dynamics of individual molecules, for example to study chemical reactions and protein folding.
While the researchers conducted an extensive survey of h-BN defects to discover ones that have special spin-dependent optical properties, the exact nature of those defects is still unknown. Next steps for the team include understanding what makes some, but not all, defects responsive to magnetic fields, and then recreating those useful defects.
Some of that work will be enabled by Penn’s Singh Center for Nanotechnology and its new JEOL NEOARM microscope. The only transmission electron microscope of its kind in the United States, the NEOARM is capable of resolving single atoms and potentially even creating the kinds of defects the researchers want to work with.
“This study is bringing together two major areas of scientific research,” Bassett says. “On one hand, there’s been a tremendous amount of work in expanding the library of 2D materials and understanding the physics that they exhibit and the devices they can make. On the other hand, there’s the development of these different quantum architectures. And this is one of the first to bring them together to say ‘here’s a potentially room-temperature quantum architecture in a 2D material.’”
This work was supported by the Army Research Office (W911NF-15–1–0589) the Australian Research Council (DE170100169) and the National Science Foundation through the Materials Research Science and Engineering Center Program (DMR-1720530) and the National Nanotechnology Coordinated Infrastructure Program (NNCI-1542153)


OCTOBER 2, 2019 by Vienna University of Technology
Energy is a quantity that must always be positive—at least that’s what our intuition tells us. If every single particle is removed from a certain volume until there is nothing left that could possibly carry energy, then a limit has been reached. Or has it? Is it still possible to extract energy even from empty space?
Quantum physics has shown time and again that it contradicts our intuition, which is also true in this case. Under certain conditions, negative energies are allowed, at least in a certain range of space and time. An international research team at the TU Vienna, the Université libre de Bruxelles (Belgium) and the IIT Kanpur (India) have now investigated the extent to which negative energy is possible. It turns out that no matter which quantum theories are considered, no matter what symmetries are assumed to hold in the universe, there are always certain limits to “borrowing” energy. Locally, the energy can be less than zero, but like money borrowed from a bank, this energy must be “paid back” in the end.
“In the theory of General Relativity, we usually assume that the energy is greater than zero, at all times and everywhere in the universe,” says Prof. Daniel Grumiller from the Institute for Theoretical Physics at the TU Wien (Vienna). This has a very important consequence for gravity: Energy is linked to mass via the formula E=mc². Negative energy would therefore also mean negative mass. Positive masses attract each other, but with a negative mass, gravity could suddenly become a repulsive force.
Quantum theory, however, allows negative energy. “According to quantum physics, it is possible to borrow energy from a vacuum at a certain location, like money from a bank,” says Daniel Grumiller. “For a long time, we did not now about the maximum amount of this kind of energy credit and about possible interest rates that have to be paid. Various assumptions about this “interest” (known in the literature as “Quantum Interest”) have been published, but no comprehensive result has been agreed upon.
The so-called “quantum null energy condition” (QNEC), which was proven in 2017, prescribes certain limits for the “borrowing” of energy by linking relativity theory and quantum physics: An energy smaller than zero is thus permitted, but only in a certain range and only for a certain time. How much energy can be
borrowed from a vacuum before the energetic credit limit has been exhausted depends on a quantum physical quantity, the so-called entanglement entropy.
“In a certain sense, entanglement entropy is a measure of how strongly the behavior of a system is governed by quantum physics,” says Daniel Grumiller. “If quantum entanglement plays a crucial role at some point in space, for example close to the edge of a black hole, then a negative energy flow can occur for a certain time, and negative energies become possible in that region.”
Grumiller was now able to generalize these special calculations together with Max Riegler and Pulastya Parekh. Max Riegler completed his dissertation in the research group of Daniel Grumiller at the TU Wien and is now working as a postdoc in Harvard. Pulastya Parekh from the IIT in Kanpur (India) was a guest at the Erwin Schrödinger Institute and at the TU Wien.
“All previous considerations have always referred to quantum theories that follow the symmetries of Special Relativity. But we have now been able to show that this connection between negative energy and quantum entanglement is a much more general phenomenon,” says Grumiller. The energy conditions that clearly prohibit the extraction of infinite amounts of energy from a vacuum are valid for very different quantum theories, regardless of symmetries.
The law of energy conservation cannot be outwitted
Of course, this has nothing to do with mystical “over unity machines” that allegedly generate energy out of nothing, as they are repeatedly presented in esoteric circles. “The fact that nature allows an energy smaller than zero for a certain period of time at a certain place does not mean that the law of conservation of energy is violated,” stresses Daniel Grumiller. “In order to enable negative energy flows at a certain location, there must be compensating positive energy flows in the immediate vicinity.”
Even if the matter is somewhat more complicated than previously thought, energy cannot be obtained from nothing, even though it can become negative. The new research results now place tight bounds on negative energy, thereby connecting it with quintessential properties of quantum mechanics.
More information: Daniel Grumiller et al. Local Quantum Energy Conditions in Non-Lorentz-Invariant Quantum Field Theories, Physical Review Letters (2019).
Journal information:Physical Review Letters
Provided by Vienna University of Technology


Physicists have just upped their ante: Not only have they split atoms but, even trickier, they've put them back together.
Their secret? Quantum physics. A team of scientists was able to "split" an atom into its two possible spin states, up and down, and measure the difference between them even after the atom resumed the properties of a single state.
The research wasn't just playtime for quantum physicists: It could be a steppingstone toward the development of a quantum computer, a way to simulate quantum systems (as plant photosynthesis and other natural processes appear to be) that would help solve complex problems far more efficiently than present-day computers can.
The team at the University of Bonn in Germany did a variation on the famous double-slit experiment, which shows how ostensibly solid particles (atoms, electrons and the like) can behave like waves. The researchers found that they could send an atom to two places at once, separated by 10 micrometers (a hundredth of a millimeter — a huge distance for an atom). [Graphic: Nature's Tiniest Particles Explained]
In the classic double-slit experiment, atoms are fired at a wall with two breaks in it, and they pass through to the other side, where they hit a detector, creating the kind of interference pattern expected from a wave. If atoms behaved the way we intuitively expect particles to behave, they should emerge out of one slit or the other, with no interference pattern. As more and more atoms passed through the slits, there should be a cluster of them around the two points behind the slits.
Since this is quantum mechanics, that's not what happens.
Instead, there's an interference pattern that shows peaks and valleys. The atoms behave like light waves. The atom is in two places at once.
But if you try to see the atom in one or both places, it "collapses" into one, as the act of observing it determines its fate; hence, the interference pattern disappears.
In the experiment at Bonn, the researchers fired two lasers in sequence at a single atom of cesium, moving it to the left or right. The lasers allowed the researchers to control the movement of the atom precisely, in a way that the old-fashioned double slit would not. (Before firing the lasers, the researchers cooled the atom to within a hair of absolute zero, eliminating most of its own movement.)
Each atom has a spin state, which is either up or down. By moving the atom in two directions at once (using both lasers), the scientists were able to make it "split." Unlike splitting an atom into its constituent subatomic particles, as happens in radioactive decay, in this case the atom was essentially splitting into a set of twins. It was in two states at once — up and down. [Twisted Physics: 7 Mind-Blowing Findings]
It's not possible to see both states at once. If one were to try to measure the state of the atom, it would "collapse" into a single state. But when one looks at the atom at the end of its journey, the combination of the two states can be measured.
Since atoms — and other quantum particles — behave like waves, they have phases, just as waves do. (The phase is the particular point in the cycle of a wave, and is measured by degrees. Two waves that are the same shape and 180 degrees out of phase with each other will cancel each other out as one's trough aligns with the other's crest. Waves in phase with each other will add up as one crest aligns with the other crest).
The laser distorts the wave phase when it moves the atom to the left or right. So there is now a difference in the phases of the two spin states when the atom arrives at its destination and is no longer "split." Even though it's not possible to see both states at once, when one looks at the atom at the end of its journey, the combination of the two states can be measured.
In addition to measuring that phase difference, the researchers also saw "delocalization" — the double path through space the atom takes — at a greater distance than ever before, on the scale of micrometers as opposed to nanometers.
It's this dual nature, called a superposed state, of atoms that would make quantum computers so powerful. The bits (known as "qubits") could be in more than one state at once, allowing for calculations that would take ordinary computers an extremely long time. It also means that quantum computers could be useful for simulating other quantum systems.
Physicist Andrea Alberti, one of the paper's co-authors, said that's why in the future the researchers want to experiment with more atoms. "With two atoms, you have four different trajectories, but only one is where they are 'meeting,'" he said. By controlling the phase of more atoms, you have more bits. One could think of it as two bits in all four possible states at once.
It isn't clear, he said, what minimum number of bits would be needed to make a working quantum computer. But the fact that scientists can control the phase states of a single atom means it should be possible to do the same thing with more than one.
The point, Alberti said, is to build a way of simulating quantum systems. Right now that is difficult because the calculations are so complex. But a quantum computing system lends itself to such calculations better than a classical computer does.
Copyright 2012 LiveScience, a TechMediaNetwork company. All rights reserved. This material may not be published, broadcast, rewritten or redistributed.


The next generation of computers is a few years off, but it’s pretty damn cool.
It’s like no computer you’ve ever seen, nor are you likely to ever own. It promises speed and the ability to tackle problems ordinary computers can’t handle.
The machine is the D-Wave 2X, and the only working model outside the company is in the Quantum Artificial Intelligence Lab. A joint project between Google, NASA, and the Universities Space Research Association, the lab will test-drive the 2X on some sticky problems in high-powered computing.
The 2X is a type of quantum computer, which means it uses devices that exploit quantum physics to replace transistors and other components of ordinary computers. The quantum nature of the inner workings in theory should make the computer solve problems much faster than anything else available, making it useful for a wide range of applications. While there are no fully quantum computers out yet, the 2X is the closest yet—assuming it works as advertised.
All ordinary computers—laptops, desktops, tablets, phones, e-readers, smartwatches, or whatever – are based on semiconductors, materials that conduct electricity reluctantly. That reluctance makes it easy to control the flow of power using devices like transistors, so that current is either flowing or not: represented by the numbers “1” for “on” or “0” for “off.” Combining the current through different parts of circuits allows computers to perform simple mathematical operations using just those two numbers. The power of a computer lies in doing lots and lots and lots of computations, faster than we perceive. (Note to experts: this is a simplified explanation. Don’t try this at home, kids!)
Quantum computers also use just two numbers, but instead of manipulating electric current, they manipulate “quantum states.” A quantum state contains a kind of list of all the possible configurations a particle (or other microscopic system) can have: its position, speed, energy, spin, and so forth. When two quantum systems interact with each other, or we perform a measurement in the lab, the quantum state describes how likely the outcome of that interaction or measurement was.
Until the measurement, though, the state is undetermined. For a quantum computer, a “quantum bit” or “qubit” could be either 0 or 1, but we don’t know until the computer reads it out in some way. One qubit, just like one bit in a normal computer, is pretty useless. However, if you have lots of qubits, you can perform many calculations simultaneously. Theoretically, a quantum computer could solve a given problem every possible way, including finding all the wrong solutions, in the amount of time it would take a normal computer to find a single solution to the same problem. That makes quantum computers useful for stuff like decryption and finding the optimal approach to performing searches.
But “theoretically” is the key word. Nobody has yet built a true quantum computer, and the D-Wave 2X is no exception. (More about what it is shortly.) One difficulty is that quantum states are delicate things: interactions between particles behave exactly the same way a measurement does, altering the state and screwing up whatever calculation we were trying to do. A larger problem is that all qubits in the computer need to be entangled with each other, meaning that their quantum states are linked up: a measurement on one qubit restricts the possible outcome of similar measurements on all the others. The more qubits, the harder the entanglement becomes.
To minimize such snafus, the 2X and similar devices run at very cold temperatures, to keep ambient vibrations and other noise to a minimum. We’re talking very cold: the D-Wave 2X at Google’s Quantum Artificial Intelligence Lab has to run at 0.015 degrees Celsius above absolute zero, or 15 millikelvins. (For comparison, the ambient temperature of outer space is 2.7 degrees above absolute zero.) Even with that, the 2X isn’t the ideal quantum computer described by theory – D-Wave describes it as a “quantum optimizer” instead – and some people are still skeptical it’s doing fully quantum calculations.
The D-Wave 2X uses over 1000 superconducting qubits, linked in a circuit resembling ordinary computer processors. Rather than trying to solve all the difficulties of quantum computing in one go, the 2X is an “adiabatic quantum optimizer.” In principle, you feed it the mathematical representation of the problem you want to solve, and the qubits adjust to find the quantum configuration that corresponds to the solution. This is a standard solution technique called “annealing,” but in a normal computer the configuration is simulated, rather than worked out using actual quantum systems. In my physics research days, I wrote programs like this on ordinary computers.
It’s a fascinating idea, and one that looks very promising. However, there’s some disagreement over whether D-Wave’s machines are working as advertised. Ordinary benchmarks used to measure a computer’s speed haven’t found a noticeable improvement from going quantum. D-Wave engineers say that we should be using a different set of benchmarks instead, since the way the 2X processes is fundamentally different.
The real proof is in the results. If the 2X or other quantum computers can solve problems that are either too hard or too slow on ordinary computers, then we’ll call it a victory for the next generation of computers. And that is pretty damn cool.


The six stages of quantum networks
Quantum networks will go through different stages of development until they reach their full functionality. Recently, researchers from QuTech proposed a roadmap towards a full quantum internet, detailing six stages of development that are determined by the functionality available to the end nodes in the network.
The initial stage is that of trusted repeater networks. In these networks, end nodes that are directly connected can perform quantum key distribution, and end nodes that are connected by a chain of intermediate repeaters can also establish a secure key, provided that the intermediate repeaters are trusted. This stage can be regarded as a pre-quantum network, or zeroth stage, since no quantum information is exchanged between end nodes.
Stages 1 and 2
The first truly quantum stage, prepare and measure networks, makes the end-to-end delivery of qubits possible. This allows for instance to perform quantum key distribution between any two end nodes or secure login (see pages 17 and 34-35).
The second stage, entanglement distribution networks, allows for the distribution of entanglement between arbitrary nodes in the network. In this stage it becomes possible to implement the device independent version of quantum key distribution, based on entanglement (see page 17).
The first and second stages can be seen as stages of a proto-quantum networks since they make the first applications for quantum internet available. The next three stages enable further applications and are therefore advanced quantum networks.
Instead of classical nodes, a proto-quantum network has quantum nodes (quantum repeaters - the blue blocks in the illustration) installed along the line. Such a network allows for direct communication between two parties; this is not possible in the pre-quantum network. Quantum key distribution enables completely secure communication, since quantum
nodes – unlike classical nodes – do not learn the key while refreshing the signal.
A quantum network with direct communication between the end nodes (end-to-end entanglement) is called an entanglement distribution network. In 2015, an entanglement distribution network covering a short distance was demonstrated in Delft. The two end nodes at positions A and B were placed 1.28 km apart. Entanglement between the end-nodes A and B was provided through position C.
An entanglement distribution quantum network enables the implementation of several tasks. Notably quantum key distribution, but also more mundane ones such as coordinated strategies to win online games.
What is a quantum memory
A quantum internet needs a memory to store the states of qubits. Such a quantum memory can be compared to the short-term memory that a classical computer uses to speed up the access to a program, the cache memory.
Without a quantum memory, a large quantum network would not be possible. Many protocols require memories and all network links would have to be established nearly simultaneously, which is very unlikely in larger networks. Any failure would mean that all quantum superpositions are lost and need to be re-created from the start. A quantum memory allows for the network to be established step by step, while storing the precious quantum states. This enables, for example, reliably sending quantum states by quantum teleportation.
How long a quantum memory should be able to store a qubit state depends on the time it takes for the communication to succeed in the rest of the network. A couple of seconds to a minute will probably be enough. While that is trivially achieved with classical bits, most types of qubits lose their state in a few microseconds. The quantum memory in the Delft quantum network can already keep superposition states for over 10 seconds. More research is underway to make sure that these quantum memories remain reliable even when the network links are operated at the same time.
Stages 3, 4 and 5
Advanced quantum networks
The third stage, memory networks, requires nodes to be able to keep quantum infor-mation in a quantum memory for a certain amount of time. At this stage, teleportation (page 25) and blind quantum computation (page 27) become possible, provided that a remote quantum computer is connected to the quantum network. In this stage, the implementation of quantum clock synchronization protocols, extending the baseline of telescopes, and quantum anonymous transmission (pages 36-37) also become possible.
To reach the fourth stage, fault-tolerant few-qubit networks, local operations and memory lifetimes need to be so good that a networked or distributed quantum computer (pages 36-37) can be implemented by connecting nodes from the network.
In the fifth and final stage, quantum computing networks, a full-fledged quantum computer is situated at each of the end nodes. In this stage, all quantum applications that we currently envision can be executed. For instance, this stage is necessary to implement quantum voting protocols.
Several pre-quantum networks are already in operation. Their quantum link is established through classical nodes, referred to as classical trusted repeaters, that are installed along the line. This setup is necessary, because quantum signals get lost when travelling through optical fibers. Typically, the classical nodes ‘refresh’ the signal at least every 100 kilometers.
Notably, Japan and China have implemented pre-quantum networks and quantum key distribution has already been performed there. This quantum key distribution, however, is not optimally secure because the classical nodes also learn the key while refreshing the signal, and need to be trusted.
Quantum network in Japan
In Japan, an operation centre in Otemachi is connected with three other places that are situated 12, 13 and 45 km away. In 2010, a secure TV conference was demonstrated between Kogenei and Otemachi by performing trusted quantum key distribution.
Quantum network in China
In China, one trusted repeater network already covers a long distance: 2000 kilometre of optical fibre connects Beijing with Shanghai. This network is being tested for banking and commercial communications, such as linking up data centres or online shopping businesses.
Advanced quantum network
The quantum nodes in advanced quantum networks are superior in functionality to those in proto-quantum networks. A lot more applications are therefore possible with such networks. The most advanced quantum network, shown in this picture, is one in which the end nodes are replaced with quantum computers.
QuTech is working on realising an advanced quantum network in the Netherlands with quantum nodes placed at Delft, The Hague, Leiden and Amsterdam. These quantum nodes will function as end nodes as well as quantum repeaters; they therefore need three properties. First, a quantum node should have a quantum memory that can robustly store qubit states. Second, it should be possible to process quantum information with high fidelity within a quantum node. Third, the quantum nodes should be able to communicate via fibres that are currently used for our classical internet.


An accurate analog clock ticks along with a constant precision and well known frequency: one tick per second. The longer you let it tick, the better to test its accuracy—10 times as long corresponds to a ten-fold improvement in any frequency uncertainty.
But is there a faster way to determine a frequency?
It turns out there is, as researchers report in Physical Review Letters.
The speed-up in frequency measurement comes from quantum mechanics. When a quantum bit is used to measure the frequency of a signal, the strange rules of quantum mechanics allow the frequency measurement to be much more accurate. The technique hinges on the ability to put the quantum bit in a superposition of its two quantum states, and then shift these states around in time with the signal.
Kater Murch, assistant professor of physics at Washington University in St. Louis, along with graduate student Mahdi Naghiloo and theory collaborator Andrew Jordan of the University of Rochester, described the technique as a “quantum magic trick.”
“It’s reminiscent of the magic tricks that involve a ball placed under one of two cups and the cups are shuffled around—except this time, the ball can be under both cups at the same time,” Murch says. “The resulting speedup in frequency measurement is astonishing. Now, by measuring for 10 times as long, the frequency uncertainty can be reduced by a factor of 100—enabling enhanced resolution of the frequency beyond any other technique of its kind.
“Earlier theory work published by the Jordan group this year has proven in two separate papers that the technique applied in this paper is the theoretical optimum that quantum mechanics allows.”
Exploiting quantum physics
The experiment involved using a superconducting quantum system where an external oscillating signal with unknown frequency caused the quantum system to undergo periodic changes. By applying quantum pulses on top of the oscillating signal, the state of the system could be controlled so that the final readout of the quantum system became highly sensitive to the precise value of the oscillation frequency.
The underlying physical source of the advantage is related to the fact that the energy of the quantum system is time-dependent, which causes the quantum states corresponding to different frequencies to accelerate away from each other, giving enhanced distinguishability in a given time.
This method permitted enhanced resolution of the frequency beyond any other technique of its kind, Jordan says.
This work is just one example of how the new field of quantum technologies uses the laws of quantum physics for technological advantage over classical physics, Jordan says. Other examples include quantum computing, quantum sensing, and quantum simulation. For those fields, the exploitation of quantum physics provides benefits such as a speed up of database search, the factoring of large numbers, or the rapid simulation of complex molecules.
Such fine-scale measurement of the frequency of a periodic signal is the fundamental ingredient in diverse applications, including MRI medical imaging devices, the analysis of light emitted from stars, and, of course, clock precision. Accelerating these measurements in a way that Murch and Jordan have demonstrated could have profound impacts in many areas.
Life before GPS
Murch and Naghiloo used timekeeping and GPS, and such constantly advancing technologies, as examples of the importance of their findings.
“In the 1700s, accurate clocks were the main limitation to ocean navigation.”
“Nowadays, most of us carry a phone in our pocket that is capable of telling us almost exactly where we are on Earth using the Global Positioning System,” Murch says. “The way this works is that your phone receives signals from several different satellites, and by timing the relative arrival of these signals it infers your position. The accuracy of the timing directly relates to the accuracy of your position—a relationship between timekeeping and navigation that has persisted for hundreds of years.
“Well before GPS, a sailor who wanted to know his location would navigate by the stars. In the Northern Hemisphere, the height of the north star will tell you your latitude, but to know your longitude, you need to keep track of the time. As the night goes on, the stars circle around the north star—the height of any star above the horizon is related to the local time, and by comparing this time to a clock set to Greenwich Mean Time, the time difference gives your longitude.”
Nautical timekeeping underscores the vitality of frequency advances.
“In the 1700s, accurate clocks were the main limitation to ocean navigation,” Murch says. “The Scilly naval disaster of 1707—one of the worst disasters in British naval history—was widely blamed on poor navigation, prompting the British government to invest heavily in precise clocks. The resulting chronometers transformed marine navigation and greatly accelerated the age of discovery.
“Advances in timekeeping continue to have profound impact on technology and fundamental science. Quantum tools, such as the quantum speedup in frequency measurement that we discovered, are necessary to push these technologies forward. This is an exciting time for quantum physics because these quantum resources are increasingly leading to practical advantages over traditional measurement approaches.”
The National Science Foundation, the Office of Naval Research, and the Army Research Office supported the work. This research used facilities at the Institute of Materials Science and Engineering at Washington University. Murch also acknowledges support from the Sloan Foundation.


Time crystals—how scientists created a new state of matter
Some of the most profound predictions in theoretical physics, such as Einstein's gravitational waves or Higgs' boson, have taken decades to prove with experiments. But every now and then, a prediction can become established fact in an astonishingly short time. This is what happened with "time crystals", a new and strange state of matter that was theorised, disproved, revamped and finally created in just five years since it was first predicted in 2012.
Crystals, such as diamond and quartz, are made of atoms arranged in a repeating pattern in space. In these new crystals, atoms also follow a repeating pattern, but in time. Because of this weird property, time crystals could one day find applications in revolutionary technologies such as quantum computing.
The story of time crystals begins in 2012 with Nobel Prize winner Frank Wilczek from MIT. As a theoretical physicist and a mathematician, Wilczek made a crucial step in transferring a key property of regular crystals – called symmetry breaking – to create the idea of time crystals.
To understand what symmetry breaking is, think of liquid water. In a water droplet, molecules are free to move about and can be anywhere within the liquid. The liquid looks the same in any direction, meaning that it has a high degree of symmetry. If the water freezes to form ice, attractive forces between the molecules force them to rearrange into a crystal, where molecules are spaced at regular intervals. But this regularity means that the crystal isn't as symmetrical as the liquid, so we say the symmetry of the liquid has been broken when freezing into ice.
Symmetry breaking is one of the most profound concepts in physics. It is behind the formation of crystals, but also appears in many other fundamental processes. For example, the famous Higgs mechanism, which explains how subatomic particles come to acquire mass, is a symmetry breaking process.
Back in 2012, Wilczek came up with a tantalising idea. He wondered if, in the same way that a crystal breaks symmetry in space, it would be possible to create a crystal breaking an equivalent symmetry in time. This was the first time the idea of a time crystal was theorised.
Such an object would have an intrinsic time regularity, equivalent to the crystal's regular pattern in space. For a time crystal, the pattern would be a continuous change back and forth in one of its physical properties, a kind of heartbeat that repeats forever, a bit like a perpetual motion machine.
Perpetual motion machines, which are machines that can work indefinitely without an energy source, are forbidden by the laws of physics. Wilczek recognised this oddity of his time crystal theory and, in 2015, another group of theoretical physicists showed a perpetual motion crystal would indeed be impossible.
But this was not the end of the story. In 2016, new research showed that time crystals could still exist in theory, but only if there was some external driving force. The idea was that the time regularity would be somehow dormant, hidden from view, and that adding a little energy would bring it to life and unveil it. This solved the paradox of perpetual motion, and brought new hopes for the existence of time crystals.
Then, in the summer of 2016, the conditions to create and observe time crystals were laid out in an article in the online arXiv repository, and later published in the peer-reviewed journal Physical Review Letters. The researchers studied how a special property of particles known as quantum spin could be repeatedly reversed by an external force at regular intervals. They predicted that if they did this to a set of particles, the interactions between the particles would produce their own oscillations in the spin, creating a "driven" time crystal.
In a matter of months, two different experimental groups had taken on the challenge to create the time crystals in the laboratory. One of the teams fired laser pulses at a train of ytterbium atoms that produced oscillations in the atoms' properties, at different intervals from the pulses. This meant that the ytterbium atoms were behaving as a time crystal.
The other team focused on an entirely different system, consisting of impurities in a diamond crystal. They used microwaves to disturb the impurities at well-defined intervals, and observed the same type of time-crystal oscillations as the first team. At last, time crystals had been created and Wilczek's main ideas proven true.
The prediction, realisation and discovery of time crystals opens a new chapter in quantum mechanics, with questions about the properties of this newly found state of matter and whether time crystals might occur in nature.
The symmetry-breaking properties of ordinary crystals have lead to the creation of phononic and photonic metamaterials, deliberately designed materials that selectively control acoustic vibrations and light that can be used to boost the performance of prosthetics, or to increase the efficiency of lasers and fibre-optics. So the time symmetry-breaking properties of time crystals will likely find their way into equally novel fields, such as chrono-metamaterials for quantum computing, which uses the inherent properties of atoms to store and process data.
The story of time crystals started with a beautiful idea by a theoretical physicist, and now has culminated its first chapter with conclusive experimental evidence after a mere five years. Far from coming to an end as scientists prove their big theories, it seems physics is more alive than ever.


The dream of useful quantum computing may have just come one step closer.
Australian researchers are combining two of the hottest topics in science: quantum computing and machine learning. Specifically, they’ve succeeded in training an algorithm to predict the evolving state of a simple quantum computer. Such an understanding allows real time stabilization of the system, much as tightrope walker uses a pole for balance, according to a paper published Monday in Nature Communications. That would be a big deal for everyone – from Silicon Valley to Washington, D.C.
Quantum computing extends the familiar concept of the bit to propose the "qubit." While we usually etch transistors in silicon, the quantum analog could be a single particle such as a photon or electron. Like the transistor, this particle is able to exist in two states that correspond to 0 or 1. The difference is, the world at the quantum level looks nothing like ours. In addition to being 0 or 1, the particle can occupy a state not purely 0 or 1 but in some sense a mixture of the two. For this reason, a qubit can be much more flexible than a regular bit.
Exploiting this probabilistic messiness is the key to quantum computing.
The mathematical behavior resists simple characterization, but the general idea is that they could take advantage of a phenomenon called interference to analyze many solutions to a problem simultaneously. In the end, more likely solutions would be amplified and less likely solutions eliminated by competing qubits, much like how ocean waves can combine to make superwaves, or cancel out entirely.
This simultaneous solution testing capability makes quantum computers theoretically useful for solving certain types of problems that would usually require a brute force approach, such as factoring large numbers and encryption. However, each problem requires a specialized method, so chances we’ll someday be checking Facebook and playing games on a quantum computer are slim.
This tantalizing dream of super-fast quantum computers not bound by the standard laws of physics has hovered on the horizon for decades, but progress is slow. IBM built a functional five-qubit system, and the record belongs to USC/Lockheed-Martin’s reportedly 1098 qubit D-Wave 2X system, although the topic is so complicated that no one can say for sure if it’s working or not.
What makes it so tricky?
Quantum computing depends on its qubits doing multiple things at once, for example spinning clockwise and counterclockwise at the same time, and interfering with other qubits in a useful way. Such behavior is so rare at our level of reality as to be unimaginable, and recreating it on demand requires an exacting environment, isolated from the destabilizing influence of the outside world. The D-Wave system, for example, operates at two-one-hundredths of a degree Celsius above absolute zero.
As a rough analogy, you could imagine the activities of the qubits are like a tightrope walker at risk of being knocked off balance at any moment by a gust of wind or a lobbed tomato. To protect the walker, we can take defensive measures to block out external influences, say by erecting a glass barrier around them.
The quantum analog of falling off the tightrope is a process called "decoherence," which describes what happens when a system starts to act classically. That’s no good for a quantum computer, which depends on "coherence" for its quantum magic.
To make matters worse, in the quantum world, if we look at the tightrope walker, they fall. "To build a quantum computer," explains University of Toronto physics professor Aephraim Steinberg, "you need to be sure no information leaks out that could possibly tell which one it was,” a "0" or a "1."
In addition to isolation, the Australian team, lead by quantum physicist Michael Biercuk has made progress on a more active form of qubit aid called quantum error correction. Instead of just protecting the tightrope walker, they’re actively helping. Whenever a qubit is about to decohere, they give a stabilizing nudge with a laser or adjust the frequency of oscillation, which would be something like tweaking the angle of the tightrope or having the walker speed up, or slow down, according to Daniel Lidar, professor of electrical engineering at the University of Southern California.
Without such error correction, "quantum computing would have been dead in the water 20 years ago," Dr. Steinberg tells The Christian Science Monitor in an email, but the novel aspect of the paper is how Dr. Biercuk’s team knew what corrections to make. Remember, looking at the tightrope makes the walker fall, so we have to help while blindfolded. As Steinberg puts it, you need a clever scheme to "measure whether an error occurred, and which one, without measuring what state the qubit is actually in."
Biercuk realized that if his team could predict how the qubits would decohere, they could apply the necessary corrections in real time and keep the balancing act going. But how do you guess what a chaotic system you can’t look at is going to do in the future?
Enter machine learning
"We used algorithms which have broad applications in many fields of science and engineering, and are already widely used," Biercuk tells the Monitor in an email. "Much of the power of our finding is that existing machine learning techniques now have a role to play in building quantum tech."
Based on past data of a qubit’s behavior, the team’s algorithm was able to train itself to predict how the system would evolve in the future. The processes governing this evolution are largely random, but there are some patterns the machine is able to detect. "The random behavior we can correct contains within it what are known as "correlations" in time – such processes change in such a way as to exhibit memory of the past state of the system. It is this correlation which we learn and exploit," Biercuk explains.
First, the team trained the program using data from repeated observations of the qubits, finding out whether the tightrope walker was right handed or left handed, if the wind blows primarily from the east, or west. Of course, during observation the quantum computer is useless. To apply what the algorithm had learned, they used a technique called "multiplexing."
For a time, the trained algorithm watched the computer run, absorbing more transient aspects of the system. Was the tightrope walker sleepy that day? Was the room breezy? Then, they closed the box and immediately let the computer operate in the isolation it needs to perform useful calculations. The algorithm forecasted what would likely be happening inside the box, and the system could apply the appropriate corrections, which reportedly led to a significant improvement over previous methods.
While Best Buy may not be stocking its shelves with code-busting quantum supercomputers anytime soon, Biercuk’s method is a new approach with the potential to move the field forward. "This technique joins and nicely complements the existing arsenal of quantum error correction techniques and will undoubtedly find wide use," says Dr. Lidar, who was not involved in this research. "The marriage of machine learning and quantum error correction may prove to be an important step towards the realization of scalable quantum computing."
[Editor's note: This story has been updated to correct which quantum system holds the record for the most qubits. The current record holder is the D-Wave 2X at the USC-Lockheed Martin Quantum Computing Center.]


The next 100 years
For time immemorial, society has been fascinated with how science and technology will shape the future. Yet although it’s really exciting to contemplate how our daily lives may be transformed, we can never accurately predict the future.
History shows that unexpected breakthroughs can send science and technology down equally unexpected paths. For example, Alexander Graham Bell foresaw global telecommunication and renewable energy technologies in 1918. But no one 100 years ago could have predicted the discovery of 2D wonder materials like graphene, or the particle zoo hidden below the scale of atoms that make up the universe.
However, today’s deep understanding of the physical world does provide some clues for how physics might impact future generations. In this centenary year for the IOP, where we are celebrating the past, recognising the present and looking to the future, we ask: what could the future hold for physics and society?
Energy - Realising the potential of carbon-free fusion
Society has been harnessing atomic energy to produce electricity since 1951. Yet these nuclear reactors rely on fission, splitting uranium atoms to heat water and ultimately produce energy. The dream for nuclear power is to build nuclear reactors that instead exploit fusion – the process powering all stars, including our Sun.
Fusion would have a limitless supply of fuel, running on atoms distilled from water. It would release four times the energy of nuclear fission. Moreover, it would come with none of the risks of fission, with no possibility of a Fukushima-like nuclear meltdown and no long-lived radioactive waste.
In rural southern France, construction is underway on the biggest and most ambitious experimental fusion reactor ever conceived – ITER. ITER scientists aim to be the first to produce net energy and maintain fusion for long periods by the mid-2030s, with ITER-like fusion power plants expected to be producing electricity in the latter half of this century.
Yet if significant challenges can be overcome, smaller, more efficient designs for commercial fusion power plants might be contributing to the energy mix as early as the 2030s. As we witness the impacts of global warming and climate change, a future where fusion power can provide limitless, clean energy could be invaluable.
Space - The race to Mars
The grainy footage of Neil Armstrong’s first steps on the Moon is indelibly imprinted in the minds of those lucky enough to have witnessed what is arguably humankind’s greatest achievement. Setting foot on Mars could have an even greater impact on society back on Earth, heralding an era in which humanity may become a multi-world species and offering the possibility, albeit remote, of finding hidden alien life.
But getting there is no mean feat – half of all missions to Mars have failed since the first Soviet attempts to send probes in the 1960s, and none of these were transporting fragile, living human bodies.
Only recently has the technology been developed to send humans to the Red Planet. NASA’s Orion spacecraft is designed for deep space missions, including trips to Mars in the 2030s. Private spacecraft company SpaceX, meanwhile, could be sending its first astronauts to Mars on its Starship Hopper as early as 2024, with an even more ambitious aim of building a city on the Red Planet by 2050.
Surviving and thriving on this truly alien world will depend on technologies being developed right now, including new techniques to 3D print protective habitats, grow crops in regolith, produce oxygen from Martian atmospheric carbon dioxide, and engineer materials to protect humans from the harmful effects of ionizing radiation on Mars walks.
Quantum - A world powered by quantum computers
Governments and companies around the world are investing billions in developing quantum computers. Why? The simple answer is that quantum computers would solve certain problems by using the quantum properties of superposition and entanglement. This would allow them to consider many probable outcomes simultaneously – instead of sorting through all possible answers one by one – and arrive at an answer rapidly. In theory, quantum computers could rapidly make calculations that would bamboozle a conventional supercomputer – and thereby solve some of society’s most intractable problems. This includes developing advanced weather and climate models to help combat climate change, accelerating drug discovery to fight disease, building unhackable data security using quantum cryptography, and modelling quantum physics to lift the veil on unsolved mysteries of the quantum world.
There is however a ‘but’. Like most quantum phenomena, qubits – the smallest unit of data in a quantum computer – are incredibly delicate. Any interaction with the environment could destroy them. This makes building a quantum computer with enough stable qubits to solve practical problems a herculean task.
At present, a collaboration between Google, NASA and the Oak Ridge National Laboratory is closest, having recently announced that they have achieved a significant milestone known as 'quantum supremacy'; a threshold where quantum computers can solve problems that traditional computers simply cannot, in practical terms. Their 54-qubit quantum processor solved a problem in 200 seconds that would take the world’s fastest supercomputer 10,000 years. Though the problem has little practical application – sampling the output of a pseudo-random quantum circuit – the achievement signals the beginning of a new era in quantum computing.
Health - Physics convergence for diagnosis and treatment
Healthcare is on the cusp of transforming beyond recognition. A conflation of scientific and technological progress will reduce hospital visits through preventative medicine, improve the way patients are diagnosed and treated, and allow researchers to find new cures.
Physics will contribute to this revolution in a myriad of ways. For instance, real-time data from wearable fitness monitors, health apps and implantable health monitoring devices will be combined with genomic information, scans that probe the body at various scales and many other sources to allow AI and machine learning algorithms to predict, prevent or treat diseases. This big data approach to healthcare will represent the pinnacle of patient-centric personalised medicine.
Elsewhere, physicists will be crucial to unlocking the secrets of the brain. New quantum sensors will measure magnetic fields generated by current flow through the brain’s neural assemblies. New imaging techniques and combinations of imaging modalities will provide insights into the anatomy and function of the human brain. Sophisticated physics models of the brain will allow researchers to safely study diseases like epilepsy or stroke in silico. And neuromorphic computing techniques will offer a tool for neuroscientists to understand the dynamic processes of learning and development, while also offering the tantalising possibility of neuromorphic chips to be developed with emergent intelligence.


Barely a week goes by without reports of some new mega-hack that’s exposed huge amounts of sensitive information, from people’s credit card details and health records to companies’ valuable intellectual property. The threat posed by cyberattacks is forcing governments, militaries, and businesses to explore more secure ways of transmitting information.
Today, sensitive data is typically encrypted and then sent across fiber-optic cables and other channels together with the digital “keys” needed to decode the information. The data and the keys are sent as classical bits—a stream of electrical or optical pulses representing 1s and 0s. And that makes them vulnerable. Smart hackers can read and copy bits in transit without leaving a trace.
Quantum communication takes advantage of the laws of quantum physics to protect data. These laws allow particles—typically photons of light for transmitting data along optical cables—to take on a state of superposition, which means they can represent multiple combinations of 1 and 0 simultaneously. The particles are known as quantum bits, or qubits.
The beauty of qubits from a cybersecurity perspective is that if a hacker tries to observe them in transit, their super-fragile quantum state “collapses” to either 1 or 0. This means a hacker can’t tamper with the qubits without leaving behind a telltale sign of the activity.
Some companies have taken advantage of this property to create networks for transmitting highly sensitive data based on a process called quantum key distribution, or QKD. In theory, at least, these networks are ultra-secure.
What is quantum key distribution?
QKD involves sending encrypted data as classical bits over networks, while the keys to decrypt the information are encoded and transmitted in a quantum state using qubits.
Various approaches, or protocols, have been developed for implementing QKD. A widely used one known as BB84 works like this. Imagine two people, Alice and Bob. Alice wants to send data securely to Bob. To do so, she creates an encryption key in the form of qubits whose polarization states represent the individual bit values of the key.
The qubits can be sent to Bob through a fiber-optic cable. By comparing measurements of the state of a fraction of these qubits—a process known as “key sifting”—Alice and Bob can establish that they hold the same key.
As the qubits travel to their destination, the fragile quantum state of some of them will collapse because of decoherence. To account for this, Alice and Bob next run through a process known as “key distillation,” which involves calculating whether the error rate is high enough to suggest that a hacker has tried to intercept the key.
If it is, they ditch the suspect key and keep generating new ones until they are confident that they share a secure key. Alice can then use hers to encrypt data and send it in classical bits to Bob, who uses his key to decode the information.
We’re already starting to see more QKD networks emerge. The longest is in China, which boasts a 2,032-kilometer (1,263-mile) ground link between Beijing and Shanghai. Banks and other financial companies are already using it to transmit data. In the US, a startup called Quantum Xchange has struck a deal giving it access to 500 miles (805 kilometers) of fiber-optic cable running along the East Coast to create a QKD network. The initial leg will link Manhattan with New Jersey, where many banks have large data centers.
Although QKD is relatively secure, it would be even safer if it could count on quantum repeaters.
What is a quantum repeater?
Materials in cables can absorb photons, which means they can typically travel for no more than a few tens of kilometers. In a classical network, repeaters at various points along a cable are used to amplify the signal to compensate for this.
QKD networks have come up with a similar solution, creating “trusted nodes” at various points. The Beijing-to-Shanghai network has 32 of them, for instance. At these waystations, quantum keys are decrypted into bits and then reencrypted in a fresh quantum state for their journey to the next node. But this means trusted nodes can’t really be trusted: a hacker who breached the nodes’ security could copy the bits undetected and thus acquire a key, as could a company or government running the nodes.
Ideally, we need quantum repeaters, or waystations with quantum processors in them that would allow encryption keys to remain in quantum form as they are amplified and sent over long distances. Researchers have demonstrated it’s possible in principle to build such repeaters, but they haven’t yet been able to produce a working prototype.
There’s another issue with QKD. The underlying data is still transmitted as encrypted bits across conventional networks. This means a hacker who breached a network’s defenses could copy the bits undetected, and then use powerful computers to try to crack the key used to encrypt them.
The most powerful encryption algorithms are pretty robust, but the risk is big enough to spur some researchers to work on an alternative approach known as quantum teleportation.
What is quantum teleportation?
This may sound like science fiction, but it’s a real method that involves transmitting data wholly in quantum form. The approach relies on a quantum phenomenon known as entanglement.
Quantum teleportation works by creating pairs of entangled photons and then sending one of each pair to the sender of data and the other to a recipient. When Alice receives her entangled photon, she lets it interact with a “memory qubit” that holds the data she wants to transmit to Bob. This interaction changes the state of her photon, and because it is entangled with Bob’s, the interaction instantaneously changes the state of his photon too.
In effect, this “teleports” the data in Alice’s memory qubit from her photon to Bob’s. The graphic below lays out the process in a little more detail:
Researchers in the US, China, and Europe are racing to create teleportation networks capable of distributing entangled photons. But getting them to scale will be a massive scientific and engineering challenge. The many hurdles include finding reliable ways of churning out lots of linked photons on demand, and maintaining their entanglement over very long distances—something that quantum repeaters would make easier.
Still, these challenges haven’t stopped researchers from dreaming of a future quantum internet.
What is a quantum internet?
Just like the traditional internet, this would be a globe-spanning network of networks. The big difference is that the underlying communications networks would be quantum ones.
It isn’t going to replace the internet as we know it today. Cat photos, music videos, and a great deal of non-sensitive business information will still move around in the form of classical bits. But a quantum internet will appeal to organizations that need to keep particularly valuable data secure. It could also be an ideal way to connect information flowing between quantum computers, which are increasingly being made available through the computing cloud.
China is in the vanguard of the push toward a quantum internet. It launched a dedicated quantum communications satellite called Micius a few years ago, and in 2017 the satellite helped stage the world’s first intercontinental, QKD-secured video conference, between Beijing and Vienna. A ground station already links the satellite to the Beijing-to-Shanghai terrestrial network. China plans to launch more quantum satellites, and several cities in the country are laying plans for municipal QKD networks.
Some researchers have warned that even a fully quantum internet may ultimately become vulnerable to new attacks that are themselves quantum based. But faced with the hacking onslaught that plagues today’s internet, businesses, governments, and the military are going to keep exploring the tantalizing prospect of a more secure quantum alternative.


/ The world based on numbers and relations /
11:15, restate my assumptions: 1. Mathematics is the language of nature; 2. Everything around us can be represented and understood through numbers; 3. If you graph these numbers, patterns emerge. Therefore: There are patterns everywhere in nature.
– Max Cohen
Mathematics (from the Greek word: mathema) means knowledge, study, learning and includes the study of such topics as quantity, structure, space and change. It seek and use patterns to formulate new conjectures; they resolve the truth or falsity of conjectures by mathematical proof. When mathematical structures are good models of real phenomena, then mathematical reasoning can provide insight or predictions about nature. Through the use of abstraction and logic, mathematics developed from counting, calculation, measurement, and the systematic study of the shapes and motions of physical objects. Practical mathematics has been a human activity from as far back as written records exist.
The research required to solve mathematical problems can take years or even centuries of sustained inquiry. The brightest minds in history have used mathematics to lay the foundation for now we measure and understand our universe.
Time and time again, we have proved that it only takes one simple formula to alter the course of humanity:
Isaac Newton’s Law of Universal Gravitation
Newton’s law explains why the planets move the way they do and how gravity works, both on Earth and throughout the universe. First published in the ”Principia” in July 1687, the Law of Universal Gravitation was the defacto reference equation for nearly 200 years until Einstein’s Theory of General Relativity replaced it.
Albert Einstein’s Theory of Relativity
Einstein’s most famous undertaking is the generally accepted theory on the relationship between space and time. First proposed in 1905, the Theory of Relativity has both radically altered the course of physics and deepened our knowledge of the universe’s past, present and future.
The Pythagorean Theorem
This ancient – first recorded circa 570-495 BC – is a fundamental principle in Euclidean Geometry and the basis for the definition of distance between two points. Pythagora’s theorem also describes the relationship between the sides of a right triangle on a flat plane.
James Clerk Maxwell’s set of equations describe how electric and magnetic fields are generated and altered, both by each other and by charges and currents. First published between 1861 and 1862, they are to classical electromagnetism what Newton’s laws of motion and universal gravitation are to classical mechanics.
The Second Law of Thermodynamics
Rudolf Clausius’ law states that energy always flows from higher concentration to lower concentrations. It also states that whenever energy changes or moves, it becomes less useful. Formulated in 1865, it has led to the development of technologies like internal combustion engines, cryogenics and electricity generation.
Logarithms were introduced by John Napier in the early 17th century as a way to simplify calculations. They answer the question, ”How many of X number do we multipy to get Y number?” Logarithms were adopted by early navigators, scientists and engineers. Today, scientific calculators and digital computers do the work for us.
The calculation shown is the definition of the derivative in differential calculus, one of calculus’ two major branches. The derivative measures the rate at which a quantity is changing — if you are walking 2 km an hour, then you will change your position by 2 km every hour. In the 1600s, Newton used calculus to develop his laws of motion and gravitation.
This equation describes how the quantum state of a quantum system changes with time. Developed by Austrian physicist Erwin Schrödinger in 1926, it governs the behavior of atoms and subatomic particles in quantum mechanics. Schrodinger’s Equation paved the way for nuclear power, microchips, electron microscopes, and quantum computing.
Information theory is a branch of mathematics that studies the coding of information in the form of sequences of symbols, and the speed at which that information can be transmitted. Applications of topics within information theory include data compression and channel coding. Research in the field was also instrumental in the development of the Internet and mobile phones.
Chaos Theory is a branch of mathematics that studies complex systems whose behavior is extremely sensitive to slight changes in conditions. In essence, it shows how small alterations can lead to consequences of much greater scale. Chaos Theory has applications just about everywhere — meteorology, sociology, physics, computer science, engineering, economics, biology, and philosophy.
In particle physics, the Dirac equation is a relativistic wave equation derived by British physicist Paul Dirac in 1928. The equation also implied the existence of a new form of matter, antimatter, previously unsuspected and unobserved and which was experimentally confirmed several years later. It also provided a theoretical justification for the introduction of several component wave functions in Pauli’s phenomenological theory of spin.


During World War II the federal government launched the Manhattan Project to ensure the U.S. would possess the first atomic bomb. Seventy-five years later, America is in another contest just as vital to national security, the economy and even the future of liberal democracy. It’s the race to build the first fully operational quantum computer.
America’s leading adversaries are working urgently to develop such a computer, which uses the principles of quantum mechanics to operate on data exponentially faster than traditional computers. Such a system theoretically would have enough computing power to open the encrypted secrets of every country, company and person on the planet. It would also enable a foreign creator to end America’s dominance of the information-technology industry and the global financial system.
How does quantum computing work? In the bizarre world of quantum mechanics, electrons and photons can be in two states at once. All current computers process data in a linear sequence of one and zeros. Every bit, the smallest unit of data, has to be either a zero or a one. But a quantum bit, or “qubit,” can be a zero and a one at the same time, and do two computations at once. Add more qubits, and the computing power grows exponentially. This will allow quantum computers of the future to solve problems thousands of times as fast as today’s fastest supercomputer.
This poses a problem for most encryption systems, because they are based on math problems that would take a conventional computer centuries to solve. The encryption that protects credit-card information and bank accounts, for instance, relies on two keys. One is the “private key,” which consists of two large prime numbers only known to the bank. The “public key” sits in cyberspace and is the product of multiplying together the two “private” primes to create a semiprime. The only way a hacker could access encrypted credit card or bank information would be by factorizing or breaking down the large “public key”—often 600 digits or longer—back to the correct two numbers of the “private key.” This Herculean task simply takes too long for current computers.
A future quantum computer will be able to decrypt such systems almost instantaneously. Even Blockchain will not be able to withstand the first quantum attack if it relies on two-key encryption architecture, which protects nearly all digital information today. To understand the scale of the threat, imagine a thousand Equifax breaches happening at once.
As a September article in the journal Nature noted: “Many commonly used cryptosystems will be completely broken once large quantum computers exist.” Most quantum experts believe that such a breakthrough may only be a decade away. If quantum computers will hold the key to the global future, the U.S. needs to secure that key.
Scientists already know that quantum computing is possible. The problem now is engineering a system that takes full advantage of its potential. Since subatomic particles are inherently unstable, assembling enough qubits to do calculations takes persistence, time and resources. Quantum computers with 10 qubits already exist. A quantum computer capable of solving problems that would stump a classical computer is close at hand. Fifty qubits will mark the threshold of quantum supremacy.
Other countries understand that. While most of the work on quantum computing in the U.S. is being done by companies like Google and Microsoft , the European Union has made quantum research a flagship project over the next 10 years and is committed to investing nearly €1 billion in the effort. Australia, the U.K. and Russia have entered the quantum race, too.
But the real national leader in quantum research investment is China. This summer it launched the first satellite capable of transmitting quantum data. It’s building the world’s largest quantum research facility to develop a quantum computer specifically for code-breaking and supporting its armed forces, with quantum navigation systems for stealth submarines. Beijing is investing around $10 billion in the facility, which is to be finished in 2½ years.
Today the U.S. government spends only $200 million a year on quantum research of all kinds, spread haphazardly over a variety of agencies—from the National Security Agency to the Energy Department.
While IBM recently set a new benchmark with its 17-qubit processor, and Google insists it will reach the 50-qubit threshold before the end of this year, China is steadily advancing toward a 40-qubit prototype—and remains determined to reach “quantum supremacy.” At the same time, countries will need to revamp their encryption systems to keep up with the new quantum reality.
The U.S. can achieve both goals through a new Manhattan Project. Call it the National Quantum Initiative. Like its atomic predecessor, the new program should marshal federal government money, the efficiencies of private industry, and the intellectual capital of the nation’s laboratories and universities, while keeping everyone focused on the essential mission: winning the quantum race.
The Manhattan Project cost some $30 billion in today’s dollars. In comparison, the National Photonics Initiative has called for an additional $500 million of federal funding over five years to help the U.S. secure its grip on quantum supremacy.
Recognizing this, Congress held its first hearings on a national initiative for quantum computing on Oct. 24. Congressional leaders should now pass a bill funding a National Quantum Initiative.
Equally important is to make sure that America’s financial system, critical infrastructure and national-security agencies are fully quantum resistant. Companies and labs are currently developing algorithms and tamper-proof encryption based on quantum technology. But without a concerted and coherent national effort, it will take years for government and industry to agree on the standards for quantum-safe replacements for today’s encryption methods, and to make sure they are deployed in time to prevent a quantum attack. In a world of quantum proliferation, the risks are too great to ignore.
Since the end of World War II, the U.S. has led the world in nuclear research, making this country stronger and safer. For three decades the U.S. has been the leader in information technology, which has made Americans more innovative and prosperous. The U.S. cannot afford to lose that leadership now—not when the future hangs in the quantum balance.


Teleportation is among one of the most highly anticipated and desired scientific advances of our time. The idea that one could send anything to anyone anywhere instantly is certainly appealing, but is it possible? Yes, but not as it’s been described in science fiction (sci-fi). Today, particles have been teleported several hundred kilometers away, but not physically. Instead of physically moving the particle to a destination, it is instead recreated elsewhere, while the original is altered.
In contrast, sci-fi teleportation involves physically sending something, like a human being, to a predetermined location. While the technology in individual films vary, in many this is done by scanning a person’s body perfectly, down to the body’s sub-atomic particles’ quantum states, and then dematerializing that person and sending the scanned information to be rematerialized or reconstructed back into that original person somewhere else. However, this theory is fraught with multiple challenges, both philosophical and practical.
The most common ethical concern is that this teleportation technology could also be used to create clones. In fact, based on the description above the clones that could be made would be so perfect that there would be no possible way to tell the difference between the two, unlike biological clones. Because these copies are so perfect, it raises a number of existential questions about what a person’s identity means – if the clone is a perfect replica of the original, then aren’t they the same person?
Fortunately for philosophers, the conveniently-named No Cloning Theorem shows that it would be impossible to create these perfect clones of complex systems, like people. Much simpler systems with known attributes, like a photon, could be cloned and have been teleported by taking advantage of quantum entanglement.
Entangled particles are a set of quantum particles, like photons, that have properties that are, in a sense, co-dependent. Take, for example, the quantum property of spin. For any given particle, its spin can either be “spin up” or “spin down”, but it is impossible to know for sure without making a measurement. Interestingly, once this property of the particle is measured it does not change. This is essentially like flipping a coin. While the coin is in the air, it’s landing position is uncertain, but once it lands, it will either have a heads or tails facing up, forever.
Normally, the process of measuring the spin of one particle has no bearing on measuring the spin of any other particle in the universe. This is not true for entangled particles. Entangled particles are created such that the properties of one of the entangled particles, such as spin, must always be exactly opposite of the other when measured using the same procedure. While the two particles have interdependent properties, they are always unknown until the moment that they are measured.
Once one of the entangled particle is measured, the other unmeasured, entangled particle will immediate assume the opposite spin orientation. The incredible phenomenon of quantum entanglement not only allows for rapid information transfer, but also makes teleportation possible.
Entanglement and its properties are most easily explained with the previous example of flipping a coin. This time, imagine that you’ve flipped two, entangled quarters. As the two coins descend, you catch one and a friend catches another. Each of you catch a coin and move far away from one another without peaking at how the coins have landed. While you’re moving away from each other and have not looked at the coin, you have no way of knowing how it landed. All you can be sure of is how your friend’s coin will be the opposite of yours. As a result, when you see how the coin in your hand landed, you would immediately know how your friend’s coin landed no matter how far away your friend was or whether they had looked at their coin.
Quantum Teleportation in Practice
Today, teleportation works much differently than it is portrayed in many sci-fi films. As discussed above, teleportation is unable to replicate complex systems, like people, or physically transport an object. What teleportation can do, however, is transmit detailed information quickly over large distances. Though this technology is still in its early stages, it holds a lot of promise in a variety of practical applications, such as cryptography.
The biggest issue with teleportation and entanglement, as discussed thus far, is that there is no ability to choose what state will be sent where. (When two particles are entangled their spin is entirely up to chance, even though they must be opposite of each other). In order to intentionally teleport information, one needs to use at least three particles, two of which (say #1 and #2) must be entangled (EP) with one another. The third particle (#3) is the one who’s information is to be teleported to someone who has possession of #2. In order for this to work, the same person must be in possession of #1 (EP) and #3 so that they have some means of sending information to the owner of #2 (EP).
Without detailing the mathematical specifics, this process begins by making a measurement, called a Bell measurement, of #1 and #3 together. ( If #3 was measured directly then it would be irreversibly changed.)
Because particles #1 and #2 are entangled together, making this measurement will affect both of these particles. When this measurement is made, only four outcomes are possible for a given input. Once the owner of particle #1 records the outcome of the measurement, they can communicate it to the owner of #2 through some non-quantum channel (e.g. a phone). Because all outcomes are known and #1 and #2 have opposite properties of the other, the owner of #2 can change their particle to an identical version of #3 using a relatively mathematical operation. Thus, #3 has been “teleported”.


Two scientists at the University of Central Florida have discovered how to get a solid material to act like a liquid without actually turning it into liquid, potentially opening a new world of possibilities for the electronic, optics and computing industries.
When chemistry graduate student Demetrius A. Vazquez-Molina took COF-5, a nano sponge-like, non-flammable manmade material and pressed it into pellets the size of a pinkie nail, he noticed something odd when he looked at its X-ray diffraction pattern. The material’s internal crystal structure arranged in a strange pattern. He took the lab results to his chemistry professor Fernando Uribe-Romo, who suggested he turn the pellets on their side and run the X-ray analysis again.
The result: The crystal structures within the material fell into precise patterns that allow for lithium ions to flow easily – like in a liquid.
The findings, published in the Journal of the American Chemical Societyearlier this summer, are significant because a liquid is necessary for some electronics and other energy uses. But using current liquid materials sometimes is problematic.
For example, take lithium-ion batteries. They are among the best batteries on the market, charging everything from phones to hover boards. But they tend to be big and bulky because a liquid must be used within the battery to transfer lithium ions from one side of the battery to the other. This process stores and disperses energy. That reaction creates heat, which has resulted in cell phones exploding, hover boards bursting into flames, and even the grounding of some airplanes a few years ago that relied on lithium batteries for some of its functions.
But if a nontoxic solid could be used instead of a flammable liquid, industries could really change, Uribe-Romo said.
“We need to do a lot more testing, but this has a lot of promise,” he said. “If we could eliminate the need for liquid and use another material that was not flammable, would require less space and less packaging, that could really change things. That would mean less weight and potentially smaller batteries.”
Smaller, nontoxic and nonflammable materials could also mean smaller electronics and the ability to speed up the transfer of information via optics. And that could mean innovations to communication devices, computing power and even energy storage.
“This is really exciting for me,” said Vazquez-Molina who was a pre-med student before taking one of Uribe-Romo’s classes. “I liked chemistry, but until Professor Romo’s class I was getting bored. In his class I learned how to break all the (chemistry) rules. I really fell in love with chemistry then, because it is so intellectually stimulating.”
Uribe-Romo has his high school teacher in Mexico to thank for his passion for chemistry. After finishing his bachelor’s degree at Instituto Tecnológico y de Estudios Superiores de Monterrey in Mexico, Uribe-Romo earned a Ph.D. at the University of California at Los Angeles. He was a postdoctoral associate at Cornell University before joining UCF as an assistant professor in 2013.
Learn more: UCF Team Tricks Solid Into Acting as Liquid
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