The most fundamental level in the study of matter and energy is quantum physics. It tries to learn more about the characteristics and actions of the very elements that make up nature.
The fundamental knowledge of materials, chemistry, biology, and astronomy now includes quantum insights. These findings have been a great source of innovation, leading to the development of gadgets like transistors and lasers as well as significant advancements in fields like quantum computing that were previously seen as entirely theoretical. The potential of quantum research to alter our understanding of gravity and its relationship to space and time is being investigated by physicists.
Quantum mechanics is a branch of physics that defines the behavior of particles, including atoms, electrons, photons, and nearly all molecules and sub-molecules. It serves as the theoretical cornerstone for all branches of quantum physics: quantum information science, quantum technology, quantum field theory, and quantum chemistry. The behavior of matter and radiation on an atomic scale is frequently strange, and the implications of quantum theory are so complex that require a deep understanding.
Fundamentally, radiation and matter are both made up of particles and waves. The progressive discovery by scientists of the particle-like characteristics of radiation and the wave-like characteristics of matter served as the catalyst for the creation of quantum mechanics.
History of Quantum Mechanics
According to the University of St. Andrews in Scotland, quantum mechanics has first proposed as a collection of contentious mathematical explanations for phenomena that the mathematics of classical mechanics were unable to explain. It began at the beginning of the 20th century, at the time Albert Einstein published his theory of relativity, a different revolution in physics that explains the motion of objects moving quickly. Quantum mechanics cannot be traced back to a single researcher. Instead, numerous scientists contributed to a foundation that, between the late 1800s and 1930, gradually acquired recognition and experimental proof.
Planck and Quanta
German theoretical physicist, Max Planck. He is commonly referred to as the father of quantum theory. In order to calculate the frequencies of light energy radiated from a heated object, Planck developed a new mathematical formula. It demonstrated how hot things would emit reddish frequencies. The frequencies of all visible colors would be emitted by hotter objects, giving them the appearance of glowing white. The most crucial prediction of Planck’s formula was that no ultraviolet frequencies would be released.
Planck’s original theory was that hot objects could only emit energy in discrete “packets” or tiny units at the subatomic scale (a single quantum is called a quantum). A quantum’s energy content increased with frequency, according to Planck. Lower frequencies, like red light, have less energy than higher frequencies, such as those in white light.
Bohr Model and Electron Orbitals
The popularity of quantum theory was rising. However, it remained merely a mathematical justification for some odd observations. Niels Bohr (Danish physicist) was the first to explain why energy exists in distinct packets. He presented a brand-new theory concerning the atom’s structure.
Prior to Bohr, scientists believed that an atom was composed of a positively charged nucleus with negatively charged electrons revolving around it. However, Bohr completely altered this theory. According to him, those electrons had to follow one of a number of predetermined pathways. These paths resembled the orbits of planets around the Sun, and they were known as electron orbitals to him. There is a specific energy level for each orbital.
An electron “jumps” from one orbital to the next largest orbital when it takes in enough energy. Energy is released when an electron “falls” into the next lowest orbital. The energy differential between the two orbitals is exactly reflected in the amount of energy released. This is why energy doesn’t exist on a continuous scale; instead, it exists in discrete values known as “quanta.”
Einstein and Photons
Even before Bohr, the photoelectric effect problem was resolved with the aid of quantum theory. This is the finding that illuminating a metal surface can cause electrons to fly off the metal.
A larger amplitude led to more electrons ejecting when metal was exposed to light. Moreover, electrons are ejected with greater energy in response to higher-frequency light. The renowned German physicist, Albert Einstein, had a theory. He used the quantum theory of Planck to explain light. He proposed the idea that light can occasionally act as discrete electromagnetic energy packets. He gave these bundles the name photons.
In summary, Planck saw electromagnetic radiation coming from the heated objects’ electrons as the quantized energy. In contrast, the electrons in the metal received energy from Einstein’s photons. The electron would exit its orbital and completely leave the metal if the photon energy was high enough. In this way, Bohr’s electron orbitals gave quantum mechanics a theoretical justification.
The following fundamental Ideas also contributed to laying the groundwork for quantum physics:
This idea has been around since the early days of quantum research. According to how they were measured, light and matter had the characteristics of either particles or waves, as evidenced by the results of the tests that led to this conclusion. The double-slit experiment is the most famous example of this, in which particles like electrons are fired at a board with two slits cut into it; behind the board, a screen is placed that illuminates when an electron strikes it.
Quantum physics and upcoming quantum technologies are based on entanglement. Entanglement is a phenomenon that manifests at extremely small, subatomic scales, just like other parts of quantum science. When two or more items are connected in a way that allows them to be thought of as a unified system, even when they are extremely far apart, this phenomenon takes place.
This mathematical idea illustrates the trade-off between opposing viewpoints. This indicates that two attributes of an object, such as its position, and velocity, cannot be accurately understood at the same time in terms of physics. We will only be able to determine an electron’s speed to a certain degree if we properly measure its position.
This refers to characterizing an object as a composite of several potential states existing simultaneously. In mathematical terms, superposition can be thought of as an equation that has several solutions.
The Probabilistic Nature of Quantum Objects and Mathematics
As quantum phenomena are probabilistic, maths is also required to represent them. For instance, it might not be possible to precisely pinpoint an electron’s position. Instead, it may be said to be in a variety of potential positions, each of which has a chance of containing an electron, such as within an orbital.
Mathematics is crucial to the study of quantum physics because many of its ideas are difficult, if not impossible, for us to visualize. Equations are utilized to describe or predict quantum objects and occurrences that human imaginations are capable of.
Where to start quantum mechanics? Start with Quantum Basics:
The classical intuition that serves us well in the macroscopic world but is utterly useless in the quantum realm must be ignored and unplugged in order to comprehend it. Let’s start by removing the outer layers of our traditional intuition.
Schrödinger’s Cat in a Box
In this fictitious experiment, a cat is placed in a box containing equipment that, when it detects beta particles released by a radioactive source, discharges a toxic gas.
It serves as one example of the way that quantum mechanics compels us to think. A particle exists simultaneously in every position up until it is measured, exactly like a cat that is both dead and alive.
De Broglie Wave
De Broglie waves, often known as matter waves, are any aspects of a material object’s behavior or attributes that change over time or space in accordance with the mathematical equations used to explain waves.
The concept of matter waves with wavelengths inversely proportional to particle momentum was proposed by French scientist Louis de Broglie in 1924. He claimed that each particle has its own set of matter waves, each of which has a certain wavelength.
In quantum mechanics, any particle’s wave function is a matter wave, whose shape can be calculated using the Schrödinger equation. As a result, the most significant aspect of quantum mechanics is matter waves.
Wave function Encoded Particle Information
Since the particle is a wave, its position in space is dispersed. The wavefunction, which is calculated in quantum mechanics using the Schrodinger equation, contains all of the information about particles. The probability distribution for position, momentum, spin or any other observable quantity can be described using particle wavefunctions.
Heisenberg's Uncertainty Principle
The uncertainty principle, which was developed by German physicist and Nobel laureate Werner Heisenberg in 1927, states that we cannot know a particle’s position and speed with perfect accuracy. The more precisely we can determine a particle’s position, the less we know about that particle’s speed, and vice versa.
In general, the uncertainty principle can be applied to any complementary pair of dual physical values that cannot be determined with arbitrary precision.
When first trying to understand the fundamentals of quantum mechanics, you may notice that your brain will explode at any moment. However, when you go more into the complexity and nuances of equations and observe how they apply in real life, the interest grows and reveals beauty at its most basic levels.
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Since the discovery of quantum physics, every development of particular significance has been called a "quantum leap". In computer technology, the invention of the quantum computer literally represents such a leap. But what makes it so special? What is the significance of this technological novelty? In order to clarify these and other questions, //next spoke with Dr. Roman Horsky, mathematician at the Fraunhofer Institute for Industrial Mathematics ITWM in Kaiserslautern.
For Roman Horsky, quantum computing is a key technology that will be important for many research questions in the coming years. He himself has been working on it since 2019. From his point of view, the topic has clearly picked up speed since 2020: "You can notice that movement is coming into the previously rather theoretical concept of quantum computing. For us at Fraunhofer, the technology is of great strategic importance. In June, the first IBM quantum computer on German soil was inaugurated; it is operated by Fraunhofer under local data protection law. This enables us to implement a number of research projects from different disciplines."
If you want to describe how a quantum computer works, you quickly get into the complicated terminology of higher physics: there is talk of two-dimensional complex spaces, superposition states and interference.
Roman Horsky tries to give a simple explanation: "Quantum computers - like classical computers - are first of all machines that perform calculations. Unlike classical computers, however, the minimum memory units are so small that the laws of quantum mechanics apply to them. This results in fundamental differences. The basic unit of a classical computer, the bit, can assume exactly two states: It is charged or not charged. With the qubit, the basic unit of a quantum computer, the situation is less intuitive. Here, too, there is the possibility of a reduction to two basic states, but qubits as a memory unit represent a superposition of the basic states and are entangled with each other. This makes parallel calculations possible. The classical computer, on the other hand, has to carry out its calculations one after the other."
The number and interconnection of the qubits is decisive for the performance of a quantum computer, explains the financial mathematician. With the number of qubits, its computing power increases exponentially. But this in turn is currently also the challenge: the more qubits there are in a quantum computer, the more unstable the system becomes, says Horsky. And he continues: "Currently, about 50 to 70 qubits are realised in a universal quantum computer. This does not yet result in computing power that far exceeds that of classical computers. If the number of qubits is increased further, the system will quickly become unstable at its current state. Achieving durability in computing results and processes is the greatest challenge in quantum computing. The entire technology is extraordinarily sensitive to all kinds of external influences. That's what makes it so difficult to implement in practice."
The "computing machine", which was built in Ehningen, Baden-Württemberg, is a joint project of many participants. "Together with IBM, we provide a technology in the Fraunhofer network that can also be used beyond our institutes by industry, research and politics," Horsky explains the principle. In a ticket model, external interested parties can "book in" on the quantum computer in Ehningen - currently for a low five-figure monthly fee.
It is not yet possible for a quantum computer to run in routine operation, Dr Roman Horsky continues. "You have to think of it more like a laboratory unit. The whole thing has a strongly experimental character, and many things don't work smoothly yet." He also says that the capacities of these computers are still too limited to be able to map complex models. "Nevertheless, a number of very exciting research questions can be mapped, and we are just starting with various promising research projects from both the energy and the finance sector," says the Fraunhofer ITWM employee happily.
Roman Horsky is particularly interested in questions from the financial and insurance environment. For ten years now, the graduate physicist, who completed his doctorate in financial mathematics, has been working in applications research at Fraunhofer ITWM. Together with a total of about 500 colleagues - a large part of them mathematicians, but also scientists from many other disciplines - he works on projects in the field of techno and business mathematics. "Even if it sounds theoretical, our work always has an application focus. We often work with partners in business and industry." He himself is based in the department of financial and actuarial mathematics and, among other things, looks after the possible fields of application of the quantum computer in this area. With "our own" quantum computer on German soil, it is possible to explore the potential of the technology in more detail and compare it with classical methods. "The exciting thing is that I can combine my skills from the fields of physics and financial mathematics in quantum computer technology. That fascinates me a lot," Horsky explains. The quantum computer requires a different approach to mathematical problems, he says. "The machine has specific characteristics and properties that entail a different form of ideal use. Accordingly, one needs other formulations of problems," Horsky explains.
In fact, the machine, i.e. the underlying technology, defines the type of question. Horsky's department at the Fraunhofer ITWM is currently working on three specific research projects: For the energy sector, it is about optimising the use of power plants; in the financial sector, it is about simulating capital market models; and in the insurance sector, the quantum computer is supposed to help optimise the management of fixed assets by including stochastic factors.
These and similar research projects will show how efficiently and stably the quantum computer works in application questions and what long-term perspectives can be derived for the technology.
But no matter how successful the use of the quantum computer in the Fraunhofer network will be: These machines are still a long way from being a series model. Horsky states: "It is currently quite inconceivable that at some point every household will have a quantum computer. This kind of technology will always remain very specific. Maybe one day, like in the heyday of mainframes, it will be the case that large industrial companies will afford quantum-based computing systems." At this point in time, however, this too is still purely a vision of the future. The high vulnerability of qubits requires extreme shielding of the systems. Only when this succeeds and scalability is given, one can think about an everyday use, says Dr. Horsky. The website of the Fraunhofer Gesellschaft says: "There are still considerable hurdles to the operation of a quantum computer. The highest premise is to shield the fragile quanta against all environmental influences. They need a temperature lower than in space, must be cooled down to almost absolute zero of about minus 273 degrees, only work under vacuum conditions, must be electromagnetically shielded - only then is there a chance of useful calculations. Errors can occur due to external influences such as vibrations as well as during the manipulation and reading of qubits with the help of electromagnetic waves."
Roman Horsky goes into more detail: "There are different technological approaches to quantum computing. Depending on the system, the stability increases, but at the expense of the range of applications." A distinction is made, he says, between gate-based quantum computers and so-called quantum annealers. In the latter, the qubits are arranged in a predetermined structure, which makes the system more stable. However, this structure only allows specific problems and calculations. It cannot be used freely.
For Dr. Roman Horsky, quantum computing is a future topic that is gradually growing out of its infancy: "There is a spirit of optimism," says the scientist, even though it is still a highly complex topic. The quantum computer is not simply a working tool, the handling of this technology is rather an interdisciplinary topic: "You need know-how in mathematics, physics and engineering."
Roman Horsky, at any rate, is looking forward to working with the complicated and sensitive machine in the future. "And I'm looking forward to seeing the computer up close in Ehningen soon. So far, I too only know quantum computers from illustrations in books."
Text: Sabine Haas


Quantum engineers from UNSW Sydney have created artificial atoms in silicon chips that offer improved stability for quantum computing.
In a paper published today in Nature Communications, UNSW quantum computing researchers describe how they created artificial atoms in a silicon ‘quantum dot’, a tiny space in a quantum circuit where electrons are used as qubits (or quantum bits), the basic units of quantum information.
Scientia Professor Andrew Dzurak explains that unlike a real atom, an artificial atom has no nucleus, but it still has shells of electrons whizzing around the centre of the device, rather than around the atom’s nucleus
“The idea of creating artificial atoms using electrons is not new, in fact it was first proposed theoretically in the 1930s and then experimentally demonstrated in the 1990s – although not in silicon. We first made a rudimentary version of it in silicon back in 2013,” says Professor Dzurak, who is an ARC Laureate Fellow and is also director of the Australian National Fabrication Facility at UNSW, where the quantum dot device was manufactured.
“But what really excites us about our latest research is that artificial atoms with a higher number of electrons turn out to be much more robust qubits than previously thought possible, meaning they can be reliably used for calculations in quantum computers. This is significant because qubits based on just one electron can be very unreliable.”
Professor Dzurak likens the different types of artificial atoms his team has created to a kind of periodic table for quantum bits, which he says is apt given that 2019 – when this ground-breaking work was carried out – was the International Year of the Periodic Table.
“If you think back to your high school science class, you may remember a dusty chart hanging on the wall that listed all the known elements in the order of how many electrons they had, starting with Hydrogen with one electron, Helium with two, Lithium with three and so on.
“You may even remember that as each atom gets heavier, with more and more electrons, they organise into different levels of orbit, known as ‘shells’.
“It turns out that when we create artificial atoms in our quantum circuits, they also have well organised and predictable shells of electrons, just like natural atoms in the periodic table do.”
Connect the dots
Professor Dzurak and his team from UNSW’s School of Electrical Engineering – including PhD student Ross Leon who is also lead author in the research, and Dr Andre Saraiva – configured a quantum device in silicon to test the stability of electrons in artificial atoms.
They applied a voltage to the silicon via a metal surface ‘gate’ electrode to attract spare electrons from the silicon to form the quantum dot, an infinitesimally small space of only around 10 nanometres in diameter.
“As we slowly increased the voltage, we would draw in new electrons, one after another, to form an artificial atom in our quantum dot,” says Dr Saraiva, who led the theoretical analysis of the results.
“In a real atom, you have a positive charge in the middle, being the nucleus, and then the negatively charged electrons are held around it in three dimensional orbits. In our case, rather than the positive nucleus, the positive charge comes from the gate electrode which is separated from the silicon by an insulating barrier of silicon oxide, and then the electrons are suspended underneath it, each orbiting around the centre of the quantum dot. But rather than forming a sphere, they are arranged flat, in a disc.”
Mr Leon, who ran the experiments, says the researchers were interested in what happened when an extra electron began to populate a new outer shell. In the periodic table, the elements with just one electron in their outer shells include Hydrogen and the metals Lithium, Sodium and Potassium.
“When we create the equivalent of Hydrogen, Lithium and Sodium in the quantum dot, we are basically able to use that lone electron on the outer shell as a qubit,” Ross says.
“Up until now, imperfections in silicon devices at the atomic level have disrupted the way qubits behave, leading to unreliable operation and errors. But it seems that the extra electrons in the inner shells act like a ‘primer’ on the imperfect surface of the quantum dot, smoothing things out and giving stability to the electron in the outer shell.”
Watch the spin
Achieving stability and control of electrons is a crucial step towards silicon-based quantum computers becoming a reality. Where a classical computer uses ‘bits’ of information represented by either a 0 or a 1, the qubits in a quantum computer can store values of 0 and 1 simultaneously. This enables a quantum computer to carry out calculations in parallel, rather than one after another as a conventional computer would. The data processing power of a quantum computer then increases exponentially with the number of qubits it has available.
It is the spin of an electron that we use to encode the value of the qubit, explains Professor Dzurak.
“Spin is a quantum mechanical property. An electron acts like a tiny magnet and depending on which way it spins its north pole can either point up or down, corresponding to a 1 or a 0.
“When the electrons in either a real atom or our artificial atoms form a complete shell, they align their poles in opposite directions so that the total spin of the system is zero, making them useless as a qubit. But when we add one more electron to start a new shell, this extra electron has a spin that we can now use as a qubit again.
“Our new work shows that we can control the spin of electrons in the outer shells of these artificial atoms to give us reliable and stable qubits. This is really important because it means we can now work with much less fragile qubits. One electron is a very fragile thing. However an artificial atom with 5 electrons, or 13 electrons, is much more robust.”
The silicon advantage
Professor Dzurak’s group was the first in the world to demonstrate quantum logic between two qubits in silicon devices in 2015, and has also published a design for a full-scale quantum computer chip architecture based on CMOS technology, which is the same technology used to manufacture all modern-day computer chips.
“By using silicon CMOS technology we can significantly reduce the development time of quantum computers with the millions of qubits that will be needed to solve problems of global significance, such as the design of new medicines, or new chemical catalysts to reduce energy consumption”, says Professor Dzurak.
In a continuation of this latest breakthrough, the group will explore how the rules of chemical bonding apply to these new artificial atoms, to create ‘artificial molecules’. These will be used to create improved multi-qubit logic gates needed for the realisation of a large-scale silicon quantum computer.
Research collaborators and funding
Other authors on the paper include Drs. Henry Yang, Jason Hwang, Tuomo Tanttu, Wister Huang, Kok-Wai Chan and Fay Hudson, all from Professor Dzurak’s group, as well as long-time collaborators Dr Arne Laucht and Professor Andrea Morello from UNSW. Dr Kuan-Yen from Aalto University in Finland assisted the team, while Professor Kohei Itoh from Keio University in Japan provided enriched silicon-28 wafers from which the devices were made. The qubit devices incorporated nano-scale magnets to help enable qubit operation, and these were designed with support from a team led by Professor Michel Pioro-Ladrière at Université de Sherbrooke in Canada, including his PhD student Julien Camirand Lemyre.
The project was funded with support from the Australian Research Council, the US Army Research Office, Silicon Quantum Computing Proprietary Limited, and the Australian National Fabrication Facility, with Drs Saraiva and Yang acknowledging support from Silicon Quantum Computing. The Canadian team received support from the Canada First Research Excellence Fund and the National Science Engineering Research Council of Canada.


After a long day in the sun, you may come back with burning sensations and red skin. A trip to the beach is typically associated with sunscreen or sunburn. However, it might have more to do with it than you think. From tanning booths to cancer treatment, ultraviolet light plays an integral role in our lives. If you’re getting flashbacks to your grade school science class, don’t fret. Continue reading for everything you need to know about ultraviolet radiation and how it affects you.
What is Ultraviolet Light?: Complete Explanation
Ultraviolet (UV) light is a type of electromagnetic radiation that sits just above the spectrum of light that we can see with unaided eyes. It makes up a portion of the electromagnetic spectrum, with its wave frequencies measuring less than X-rays and blending into the violet range of visible light.
The electromagnetic spectrum is typically measured in three metrics, depending on which is easiest to read. These include wavelength, frequency, and energy. Ultraviolet is typically measured in wavelength (meters) or frequency (hertz). While there’s no hard line to define the boundaries of UV, it typically ranges from 180 to 400 nanometers (nm).
Ultraviolet light has a unique energy that causes them to break chemical bonds. This results in a variety of benefits, such as purifying water systems. However, overexposure can lead to damaging consequences such as sunburn.
This portion of the electromagnetic spectrum comes from various natural and artificial sources. Its prevalence in new stars allows scientists to explore the universe as it formed. Furthermore, humans have used UV in practical applications following its discovery in the 1800s.
Ultraviolet Light: An Exact Definition
The U.S. Navy defines ultraviolet light as “part of the electromagnetic radiation spectrum,” where “electromagnetic radiation is made up of oscillating electric and magnetic fields which are propagated in free space and matter.” The military agency defines its wavelengths, which range “from approximately 180 nanometers (nm) to 400 nanometers.”
The ultraviolet spectrum varies based on its physiologic effects. The Navy breaks down UV radiation into critical ranges:
- UVA (near UV) 315 – 400nm
- UVB (middle UV) 280 – 315nm
- UVC (far UV) 180 – 280nm
Where Does Ultraviolet Light Come From?
Our sun is the largest producer of ultraviolet radiation within the range of our influence. Far UV is the most dangerous, but the atmosphere absorbs nearly all its wavelengths. It also absorbs about 95% of middle UV, which is the cause of sunburn. This is why it’s okay to be in the sun while not overexposing yourself.
In astronomy, scientists use the electromagnetic spectrum to evaluate the age and characteristics of star clusters. NASA researchers have discovered that ultraviolet images of galaxies reveal star nurseries, with young stars producing energy much more powerful than our own sun. Evaluating the universe in the ultraviolet allows us to discover how stars form.
In addition to the ultraviolet light from celestial bodies, energy waves of this type have been found in electric discharges. This occurs during the breakdown of gas and finds use in specialized lamps.
How Do You Create Ultraviolet Light?
One way to artificially produce ultraviolet light is with an electric discharge passing through a gas. Mercury vapor is the most used option in practical applications due to its consistency. The mercury vapor absorbs the UV radiation from the electric discharge and emits visible light as an exhaust.
Who Discovered Ultraviolet Light?
Ultraviolet rays were discovered in 1801 by German chemist Johann Wilhelm Ritter while searching for the polarities in the forces of nature. While experimenting in the opposite direction of William Herschel’s “heat rays,” Ritter discovered that silver chloride paper reacted to invisible frequencies faster than it did to violet.
This experiment proved the existence of wavelengths beyond the visible light spectrum, with Ritter naming the wavelength deoxidizing rays for their ability to alter the chemical balance of objects. The name was dropped near the end of the century in favor of the more accurately descriptive name ultraviolet.
What Are the Applications of Ultraviolet Light?
While too much exposure to ultraviolet can lead to sunburn, people often use the frequency in moderation to tan skin. Tanning is most effective when subjected to UV wavelengths of 280 – 315nm. This can occur naturally through sun exposure or artificially with tanning lights.
When specific objects are exposed to ultraviolet radiation, they can absorb it. UV waves that are absorbed cause the electrons within the object to increase in energy. As the electrons return to their original energy level, they emit the energy as absorbed light. This phenomenon, called fluorescence, results in some objects glowing or appearing brighter. We often see fluorescence used in safety equipment, where visibility is critical.
In addition to its effects on the skin, UVB causes the body to produce vitamin D. This vitamin helps create serotonin, which is associated with sensations of happiness and joy. The World Health Organization recommends 5-15 minutes of direct sunlight on the skin for high vitamin D levels.
Applications of Ultraviolet Light In the Real World
Psoralen Ultraviolet Light Treatment
Cancer Research UK is a nonprofit organization that’s exploring the use of ultraviolet light to treat skin conditions. Physicians use specific medicinal applications to increase the sensitivity of their patient’s skin. A UV light is directed at the condition, which slows down the growth of problem cells. Psoralen ultraviolet light treatment (PUVA) is used to treat lymphoma, psoriasis, and eczema, among other conditions.
Similar to how some objects glow fluorescent light when exposed to UV radiation, so do the atmospheric gases at the earth’s magnetic poles. The Aurora Borealis (also known as the Northern Lights) occur around the Arctic and Antarctic when ultraviolet radiation concentrates in those magnetic fields. The radiation bounces off gas particles (usually oxygen atoms), which get excited and raise energy. As the particles return to their natural level, they emit brilliant green (and sometimes red or blue) light.
Hubble Space Telescope
As part of the Great Observatories project in the 1990s, NASA launched the Hubble Space Telescope to observe the universe in visible and ultraviolet light spectrums. Equipped with cameras, spectrographs, and interferometers, the space observatory analyzes the beginnings of the universe. The Hubble Space Telescope focuses on distant points of light to explore how stars form.
Ultraviolet Light: Further Reading
With technology rapidly improving, it’s important to know how electromagnetic radiation like ultraviolet light applies. Both naturally and artificially occurring, UV positively and negatively affects us alongside the rest of the spectrum. To learn more about electromagnetic uses, check out the articles below.
- The James Webb Space Telescope: Complete History, Specs, and More – NASA’s latest telescope can observe the universe in infrared. Here’s what you need to know about it.
- Top 10 Largest Space Telescopes in Orbit – James Webb is making headlines with its stellar imagery. What other telescopes is NASA using?
- What’s the Next Big Thing in Technology? 10 Predictions From the Experts – From spaceflight to quantum computing, these 10 predictions could shape the future of technology.
Bluetooth vs Infrared: What’s the Difference? – take a look at the most prominent wireless technologies we use to communicate without daily gadgets.


In the 1960s, researchers at the science lab of the Ford Motor Company developed the superconducting quantum interference device, also known as a “SQUID.” It was the first usable sensor to take advantage of a quantum mechanical property—in this case, superconductivity.
That made the SQUID one of the first generation of quantum sensors: devices that use a quantum system, quantum properties or quantum phenomena to make a physical measurement. Physicists took the idea and ran with it, coming up with new types of sensors they continue to use and improve today.
SQUIDs have played a key role in the development of ultrasensitive electric and magnetic measurement systems and are still in use. For example, they amplify the detector signals for the Super Cryogenic Dark Matter Search. “As particle physicists, we’ve been using quantum sensing techniques for decades,” says SuperCDMS physicist Lauren Hsu of the US Department of Energy’s Fermi National Accelerator Laboratory.
But SQUIDs are no longer the only quantum sensors around. One important recent development in quantum sensing is known as quantum squeezing—a way to circumvent quantum limitations that even quantum sensors have faced in the past.
“The only way to do better is to start beating quantum mechanics.”
The first quantum sensors
Ford’s SQUIDs, which needed to be cooled to a few degrees above absolute zero, used superconducting loops to measure minuscule magnetic fields.
SQUIDs didn’t turn out to be of much use in an automobile. But not all Ford researchers were beholden to expectations that their creations would wind up in a car. “This shows you how different the world was back in the 1960s,” says Kent Irwin, a physicist at Stanford University and SLAC National Accelerator Laboratory. “These days Ford is not doing basic physics.”
A few decades later, while in graduate school, Irwin built on the idea of the Ford Company’s SQUID to develop a new quantum sensor: the first practical superconducting transition-edge sensor.
Irwin took advantage of the fact that superconducting material loses its superconductivity when it heats up, regaining its resistance at a precise temperature. By keeping a superconducting material as close as possible to this temperature limit, he could create a sensor that would undergo a significant change at the introduction of even a small amount of energy. Just a single photon hitting one of Irwin’s transition-edge sensors would cause it to shift to a different state.
The transition-edge sensor is well-known and has been adopted widely in X-ray astronomy, dark matter detection, and measurements of the cosmic microwave background radiation. “It’s very much old-school quantum 1.0,” Irwin says.
Quantum sensing for gravitational waves
A new generation of quantum sensors goes beyond quantum 1.0. Some of today’s sensors make use of more than just superconductivity: They’ve managed to use the Heisenberg uncertainty principle—usually thought of as a limitation to how well physicists can make measurements—to their advantage.
The Heisenberg uncertainty principle puts a cap on how accurately you can measure a pair of related properties. For example, the more you know about the position of a particle, the less you can know about its momentum.
Quantum squeezing takes advantage of these relationships by purposefully tipping the balance: moving all the uncertainty of a measurement to one side or the other.
Gravitational-wave detectors, such as LIGO in the US, and Virgo and GEO in Europe, have used quantum squeezing to great effect. In 2015, LIGO—the Laser-Interferometer Gravitational-wave Observatory—detected the first gravitational waves, undulations of spacetime first predicted by Albert Einstein. Once it got going, it was picking up new signs of gravitational-wave events every month.
LIGO detects gravitational waves using an interferometer, an L-shaped device in which two beams of light are set up to bounce off identical mirrors and return. Under normal conditions, the beams will arrive at the same time and cancel one another out. No signal will hit the detector.
But if a subtle outside force knocks them out of sync with one another, they won’t cancel each other out, and photons will hit the detector. If a gravitational wave passes through the two beams, it will hit one and then the other, interrupting their pattern.
LIGO’s measurements are limited by the quantum properties of the photons that make up their beams of light. At the quantum level, photons are affected by fluctuations, virtual particles popping in and out of existence in the vacuum. Those fluctuations could cause a false signal in the detector. How could LIGO researchers tell the difference?
“LIGO is using the most powerful lasers they can build, and the best mirrors they can build, and their back is against the wall,” Irwin says. “The only way to do better is to start beating quantum mechanics.”
Scientists at LIGO and other gravitational-wave detectors looked to quantum squeezing to help them with their virtual photon problem.
To generate squeezed light, researchers used a technology called an optical parametric oscillator, within which an input wave of laser light is converted to two output waves with smaller frequencies. This process entangles pairs of photons, and the resultant correlations of their properties serve to reduce uncertainty in one aspect of the arriving photons, allowing LIGO scientists to better measure another aspect, helping them sort the signal from the noise.
Since April 2019, when LIGO began running with the quantum squeezers, the observatory has been able to detect new gravitational-wave signals—signs of collisions between massive objects such as black holes and neutron stars—more frequently, going from about one detection per month to about one per week.
Quantum sensing for dark matter detection
Quantum squeezing has also recently found an application in the search for dark matter.
Dark matter has never been observed directly, but clues in cosmology point to it making up approximately 85% of the matter in the universe. There are several different theories that describe what a dark matter particle could be.
“The mass can be anywhere from a billionth the size of an electron up to a supermassive black hole,” Hsu says. “There are over 100 orders of magnitude that it can span.”
The most promising small dark matter candidates are axions. In the presence of a strong magnetic field, axions occasionally convert into photons, which can then be detected by an experiment’s sensors.
Like someone trying to find a radio station on a road trip in the middle of nowhere, they scan for a while at one frequency, to see if they detect a signal. If not, they turn the dial a little and try the next size up.
It takes time to listen to each “station” once the detector is tuned to a particular possible axion signal; the more noise there is, the longer it takes to determine whether there might be a signal at all.
The HAYSTAC experiment—for Haloscope at Yale Sensitive to Axion Cold Dark Matter—searches for axions by measuring two different components of electromagnetic field oscillations. Like LIGO, it is limited by the uncertainty principle; HAYSTAC researchers are unable to precisely measure both oscillations at once.
But they didn’t need to. Like LIGO scientists, HAYSTAC scientists realized that if they could squeeze all the accuracy into just one side of the equation, it would improve the speed of their search. In early 2021, researchers announced that at HAYSTAC, they had also succeeded at using quantum squeezing to reduce noise levels in their experiment.
Multiple groups have demonstrated promising new applications of superconducting circuit technology for axion detection.
The “RF quantum upconverter” uses devices similar to Ford’s SQUIDs to evade the Heisenberg uncertainty principle in dark-matter searches at frequencies below HAYSTAC’s searches. Another uses a technology borrowed from quantum computing—qubits—as a sensor to evade Heisenberg’s limits at frequencies higher than HAYSTAC. Although neither technology has been used in dark matter searches yet, scientists believe that they could speed searches up by several orders of magnitude.
At the current rate, it will still take axion experiments thousands of years to scan through every possible axion “station.” They may get lucky and find what they’re looking for early in the search, but it’s more likely that they’ll still need to find other ways to speed up their progress, perhaps with advances in quantum sensing, says Daniel Bowring, a Fermilab physicist who is involved in another axion search, the Axion Dark Matter Experiment.
“It’s going to take a lot of people with really good imaginations,” Bowring says.


Semiconductors are drivers of modern electronics, and they are the main enablers of our communications, computing, energy, transport, IoT systems and many more. Almost each and every device we have around us has a semiconductor in it, so no one can overestimate their importance in the world of technology. Today we’re trying to break down the notion of semiconductors, discover what’s inside this vital element and what trends are driving its development today.
A semiconductor as the name implies is a material that has electrical behavior between conductors and insulation. Conductors are substances that easily transmit electricity, while insulators poorly transmit electricity.
The semiconductor industry uses silicon as its primary material. Silicon is a good conductor, but it does not have the necessary characteristics to make a useful transistor. To change this, manufacturers add impurities to the silicon crystal structure. Impurities are atoms that do not belong to the regular arrangement of the crystal lattice. By adding these impurities, manufacturers can control how easily the electrons and holes move through the silicon.
Silicon is the basis for all modern electronic devices. Transistor technology was first developed using germanium, a semiconductor with similar properties to silicon. Germanium is still used today, but silicon is much easier to work with. Because of this, silicon is still the dominant semiconductor material.
Semiconductors are classified based on whether they are intrinsic or extrinsic. Intrinsic means that there are no impurities present in the material. Extrinsic means that the material requires doping to become conductive and therefore is considered a semiconductor.
Intrinsic semiconductors have no additional doping elements added to them. These materials do not need to be externally charged before they conduct electricity. Intrinsic semiconducting materials are often referred to as bulk materials. Examples of intrinsic semiconductors are silicon (Si) and germanium (Ge).
Extrinsic semiconductors are those that require doping to make them conductive. An example of an extrinsic semiconductor would be gallium arsenide, which is commonly used in transistors. Here, arsenic atoms have been added to the crystal structure of gallium to create positive charges called acceptor states. These states act as electron traps, causing the semiconductor to become electrically conductive.
The IT industry cannot be separated from the development of the semiconductor industry. Semiconductors examples are transistors, MOSFETs, ICs, and diodes. One of the semiconductor materials commonly used in a digital device (logic-based circuit) technology development is a transistor.
The invention of the transistor in 1947 helped in the development of second-generation computers into smaller, faster, more reliable, and more energy efficient than their predecessors. It was the era that transistors began their massive deployment which was started by Shockley until the birth of Fairchild Semiconductor which is considered as a pioneer in IC and transistor manufacturers.
In the early 1960s, successful second-generation computers began to emerge in business, universities, and in government. These second-generation computers are computers that use full transistors. From here was born the next generation of computers that use hardware-based LSI, VLSI, ULSI to supercomputers. The birth of computer networking technology as well as the Internet, which is also supported by semiconductor-based devices, brought IT technology into the modern state as we know it today.
Semiconductor has revolutionized electronic hardware, especially since the invention of the transistor. Semiconductors make hardware more compact and have better computing-related capabilities. The effect is that electronic components are now easier to obtain at affordable prices in the marketplace. This makes it easy for new developers to conduct research and innovation.
LANARS provides hardware development services for creating new products and businesses, as well as for improving existing ones.
The semiconductor, commonly known as the chipset, is the most important component. Despite their small size, semiconductor chips are the brains of an electronic system. In digital devices, the presence of semiconductors is needed to increase the speed of digital signal processing, including memory for data storage.
As we are now in the industrial era 4.0, the need for semiconductor chips continues to grow. The semiconductor industry is also considered the lifeblood that is essential in accelerating digital transformation. The development of computers, the telecommunication industry, automotive equipment, especially electric vehicles (EVs), as well as digitalization in many sectors require the readiness of the semiconductor industry to prepare the required resources.
In the midst of increasing demand for semiconductors, the global COVID-19 pandemic in 2020 hit almost the entire industry with a lockdown policy. This also has an impact on the supply of semiconductors, resulting in reduced supply, which has an impact on other industries. The affected industries include computers, Smart-TVs, smartphones, tablets, game consoles, and various electronic gadgets to the automotive industry.
On the other hand, the COVID-19 pandemic has also increased the need for computers and gadgets in line with the school-from-home or work-from-home policies. This condition causes the semiconductor price trend to rise from the 2020 period to the present time. The implication results in 2021 the major players of semiconductor chipsets such as TSMC actually reap profits caused by the shortage of global chipset supply.
According to a report from research firm TrendForce, if the top 10 chipset manufacturers combined, they will get a total revenue of US$127.4 billion in 2021. This figure is an increase of 48% compared to the previous year. As for 2022 itself, as reported by Deloitte, some observers say that semiconductor sales are expected to grow back by 10%, and could exceed US$ 600 billion for the first time in 2022. In the future, semiconductor trends will continue to be needed by various industries, although there is economic uncertainty is predicted, chipset availability is also expected to recover in 2023.
Moore's Law predicts that the number of transistors in integrated circuits (IC) will double every year, is used as a reference by the semiconductor industry to set their research and development targets. This is evidenced by the birth of microprocessor capabilities that are increasing every year. But even Moore's law will eventually meet an impenetrable limit, increasing computer performance by adding transistors has so far been done by reducing the size of the transistor so that it can fit more in the same area. A few years ago, physicist Michio Kaku noted that there was a point where the silicon material used to make the transistor — or any substitute for it — could not be reduced any further.
Several studies have initiated the use of other materials for the development of semiconductors. Third-generation semiconductor materials, such as gallium nitride (GaN) and silicon carbide (SiC), promise high-temperature resistance, high breakdown voltage, high frequency, high power, and high radiation resistance.
However, for a long time, the use of these materials was limited to a narrow range of fields due to their complex processing methods and high cost.
In recent years, breakthroughs in material growth and device fabrication have helped reduce the cost of third-generation semiconductor materials, enabling a wider range of applications. For example, SiC-based devices used for car inverters and GaN-based fast chargers appeared on the market.
Semiconductor technology trends that have also been widely discussed to improve chip capabilities include parallel computing, quantum computing, to protein computers that work with DNA.
Semiconductor is a material that has electrical properties between conductors and insulators. Semiconductors bring drastic changes in the technological development of mankind. From Shockley and Fairchild who make transistors to large manufacturers of chipset makers to giants like Intel that use semiconductors to create technology that plays a very important role in the development of computers, gadgets, household appliances, automation, telecommunications, and so on.
The technological trend proclaimed by Moore’s Law has already occurred, and it is predicted that the number of transistor densities in a wafer will also be achieved. Therefore, there are various developments carried out to maximize semiconductors such as the use of third-generation materials, quantum computing, etc. semiconductor trends will continue to be needed by various industries, although economic uncertainty is predicted, chipset or semiconductors availability is also expected to recover in 2023.


Researchers at the Paul Scherrer Institute PSI have put forward a detailed plan of how faster and better defined quantum bits - qubits - can be created. The central elements are magnetic atoms from the class of so-called rare-earth metals, which would be selectively implanted into the crystal lattice of a material. Each of these atoms represents one qubit. The researchers have demonstrated how these qubits can be activated, entangled, used as memory bits, and read out. They have now published their design concept and supporting calculations in the journal PRX Quantum.
On the way to quantum computers, an initial requirement is to create so-called quantum bits or "qubits": memory bits that can, unlike classical bits, take on not only the binary values of zero and one, but also any arbitrary combination of these states. "With this, an entirely new kind of computation and data processing becomes possible, which for specific applications means an enormous acceleration of computing power," explains PSI researcher Manuel Grimm, first author of a new paper on the topic of qubits.
The authors describe how logical bits and basic computer operations on them can be realised in a magnetic solid: qubits would reside on individual atoms from the class of rare-earth elements, built into the crystal lattice of a host material. On the basis of quantum physics, the authors calculate that the nuclear spin of the rare-earth atoms would be suitable for use as an information carrier, that is, a qubit. They further propose that targeted laser pulses could momentarily transfer the information to the atom's electrons and thus activate the qubits, whereby their information becomes visible to surrounding atoms. Two such activated qubits communicate with each other and thus can be "entangled." Entanglement is a special property of quantum systems of multiple particles or qubits that is essential for quantum computers: The result of measuring one qubit directly depends on the measurement results of other qubits, and vice versa.
Faster means less error-prone
The researchers demonstrate how these qubits can be used to produce logic gates, most notably the "controlled NOT gate" (CNOT gate). Logic gates are the basic building blocks that also classical computers use to perform calculations. If sufficiently many such CNOT gates as well as single-qubit gates are combined, every conceivable computational operation becomes possible. They thus form the basis for quantum computers.
This paper is not the first to propose quantum-based logic gates. "Our method of activating and entangling the qubits, however, has a decisive advantage over previous comparable proposals: It is at least ten times faster," says Grimm. The advantage, though, is not only the speed with which a quantum computer based on this concept could calculate; above all, it addresses the system's susceptibility to errors. "Qubits are not very stable. If the entanglement processes are too slow, there is a greater probability that some of the qubits will lose their information in the meantime," Grimm explains. Ultimately, what the PSI researchers have discovered is a way of making this type of quantum computer not only at least ten times as fast as comparable systems, but also less error-prone by the same factor.
Text: Paul Scherrer Institute/Laura Hennemann
The Paul Scherrer Institute PSI develops, builds and operates large, complex research facilities and makes them available to the national and international research community. The institute's own key research priorities are in the fields of matter and materials, energy and environment and human health. PSI is committed to the training of future generations. Therefore about one quarter of our staff are post-docs, post-graduates or apprentices. Altogether PSI employs 2100 people, thus being the largest research institute in Switzerland. The annual budget amounts to approximately CHF 400 million. PSI is part of the ETH Domain, with the other members being the two Swiss Federal Institutes of Technology, ETH Zurich and EPFL Lausanne, as well as Eawag (Swiss Federal Institute of Aquatic Science and Technology), Empa (Swiss Federal Laboratories for Materials Science and Technology) and WSL (Swiss Federal Institute for Forest, Snow and Landscape Research).
"Now it's time for something new" - An interview from 30 January 2019 with Gabriel Aeppli and Christian Rüegg about new solutions for better computers and data storage systems.
Condensed Matter Theory Group
Paul Scherrer Institute, Forschungsstrasse 111, 5232 Villigen PSI, Switzerland
Telephone: +41 56 310 27 78;
e-mail: firstname.lastname@example.org [German, English]
Universal Quantum Computing Using Electronuclear Wavefunctions of Rare-Earth Ions
M. Grimm, A. Beckert, G. Aeppli, M. Müller
PRX Quantum 21 January 2021 (online)


Image: Dane Wirtzfeld/iStockphoto
Ever since the laser saw the light of day a half century ago, researchers have been playing with the idea that something similar could be created using sound rather than light. But the concept made little headway in the ensuing decades. In 2009, the situation changed abruptly, when scientists at Caltech and the University of Nottingham, in England, using tiny drums and stacked semiconductors, respectively, employed conventional lasers to stimulate or probe the emission of a stream of “phonons”—the quasiparticles of sound—proving that phonon lasers, or “sasers,” were indeed a sound idea.
Now researchers at NTT Basic Research Laboratories, in Japan, have taken a significant step forward by fabricating an entirely electromechanical resonator on a chip that also eliminates the need for the lasers that previous devices required. This advance makes integration with other devices easier, and applications like extremely high-resolution medical imaging and compact, low-power, high-frequency clock-pulse generators are now within reach, say its inventors.
The word laser is an acronym for “light amplification by stimulated emission of radiation.” A laser works by exciting electrons around an atom to higher levels, which then shed the extra energy in the form of photons. This activity takes place in an optical resonator, which is essentially an enclosed chamber, typically with mirrors at either end. The trapped photons bounce back and forth, stimulating the emission of more photons of the same wavelength, some of which are allowed to escape in a controlled beam of laser light.
“In our approach to the saser, we replaced the optical resonator with a microelectromechanical resonator, or oscillator, that moves up and down and produces a spectrum of discrete sonic vibrations, or phonon modes,” says Imran Mahboob, a researcher at NTT. “Simply put, we’re creating an electromechanical atom that we then jiggle to produce the phonons.”
The resonator consists of a micrometer-scale gallium arsenide bar (250 x 85 x 1.4 micrometers) called a beam, which is suspended above a gap in a semiconductor chip and whose oscillations are controlled with piezoelectric transducers. An alternating voltage applied to the beam’s terminals induces alternating expansion and compression. In this scheme, the bar plays the part of an optical resonator, while three levels of oscillating tones or modes (high, middle, and low) mimic the changing of the electron energy levels of the atoms in a specific type of optical laser, generating phonons in the process. When the high state is excited, it generates phonon emissions in the middle and low states. With some fine-tuning of the system, so that the sum frequency of the middle and low states matches the high mode, emission in the low mode is resonantly enhanced, and a precise, highly stable phonon beam is produced, with fluctuations limited to one part in 2 million.
Because the mechanical oscillations are extremely tiny, existing at the subnanometer level, “we place everything into a cryogenic environment with a temperature of around 2 kelvin to make them easier to observe,” says Mahboob. “This also ensures that the different resonance modes are precise, because if [the device is] hot, their frequencies would broaden and overlap so that the sum frequency of the middle and low states wouldn’t always match the high state.”
Well-Balanced Beam: A gallium arsenide resonator is the heart of NTT's phonon laser.Image: NTT
Notably, an output signal is observed only when the input voltage exceeds a specific figure. This threshold voltage is a signature feature of optical lasers, as is a large improvement in the beam’s frequency precision when phonon lasing is triggered. “So we’re convinced we have phonon lasing,” says Mahboob.
As for how such a laser could be used, he says that the device’s compactness, low energy consumption, and the possibility of high frequency give it the potential to replace the relatively bulky quartz-crystal resonators used to provide stable frequencies for synchronized operations and precise timekeeping in computers and other electronic equipment. Superior medical ultrasound imaging is another possible application, and Mahboob speculates that one day the laser might be used as a medical treatment.
Hiroshi Yamaguchi, an NTT senior distinguished researcher, also points out that by increasing the frequency of the oscillating states, the resonator could potentially be manipulated to store a discrete number of phonons. “This could open up new avenues to explore quantum cryptography and quantum computing,” he says, “as well as having the potential of enabling us to study quantum effects at the macro level.”
But before such speculations can be seriously investigated, the researchers admit they must first overcome a major challenge. Whereas optical lasers can travel through a vacuum, a phonon beam requires a medium. In this research, the sound propagates through the semiconductor crystal, and the researchers are now working out how to handle this limitation.
“On the other hand, the technology does have the advantage [in] that it’s a compound semiconductor,” points out Yamaguchi. “So it could, for example, easily be integrated with an optical device and an electrical device all on the same chip and, of course, integrated with a variety of systems. We believe this is a major advantage of our device.”
Other phonon laser researchers have been improving their devices, too. Tony Kent, a professor of physics at the University of Nottingham who is working with semiconductor stack devices to realize sasers, has been working on using them for applications that need frequencies in the hundreds of gigahertz or even terahertz frequencies. “Our main focus is exploring applications for a terahertz saser as a stable, low-noise reference or local oscillator, for use in communications, medical imaging, and security screening, and as a source for acoustic sensors of nano-objects,” he says.
Kent says that while he expects the NTT research to have a major impact on the fundamental science of micromechanical systems, he questions the practicality of some of the applications that are being suggested.
Putting aside the problem of having to work with low temperatures, and the difficulty getting the sound out of the resonator and into the semiconductor crystal, the reported beam device works at a frequency of only around 1 megahertz,” says Kent. “Yet there are already technologies generating acoustic signals for ultrasound measurement available now with frequencies higher than 1 GHz.”
About the Author
John Boyd covers technology in Japan. In April 2013, he reported on the test of new silicon carbide power electronics in the Tokyo subway system.


Keep yourself updated.
Quantum computing is a novel paradigm for computing that was introduced as a concept in the 1980s and has enjoyed a lot of attention in the recent years as the research and development for building actual quantum computers has started to bear fruit. Quantum computing holds great promise for solving some of the most difficult computational problems. It is expected to bring major advantages, for example, for drug development, weather forecasting, different kind of optimizations problems, etc. Unfortunately, quantum computing also has a darker side; If large enough quantum computers become reality, then they may solve the computational problems that are the basis of modern computer security.
Specifically, a quantum algorithm introduced by Peter Shor in the mid-1990s and subsequently called the Shor's algorithm can perform integer factorisation and find discrete logarithms in polynomial time (that is to say, significantly faster than what is possible with classical computers). RSA and Elliptic Curve Cryptography (ECC), which together cover practically all currently deployed public key cryptosystems, are based on integer factorisation and discrete logarithms, respectively. Consequently, quantum computing poses a threat to RSA and ECC and the security of the modern computation and communication infrastructure as a whole. The state-of-the-art of quantum computers is still far from being able to break practical cryptosystems, and certain difficult technical problems must be solved before quantum computers can be scaled to the sizes that pose a practical threat. Nevertheless, the threat of quantum computing must be taken seriously and it must be addressed pro-actively because often data needs to remain secure for decades and also rolling any new cryptosystems into practical use takes a long time.
Despite the gloomy sky, it is important to understand that not all cryptography is at risk and that is a clear roadmap for protecting systems even in the era of quantum computing. First of all, symmetric cryptography (for example, AES or ChaCha20) are not affected by quantum computing in any significant way – there exist a quantum algorithm called Grover's algorithm which solves generic search problems faster and, consequently, affects also symmetric cryptography, but it can be countermeasured by doubling the key lengths. That is, you can just use 256-bit keys in systems where you currently use 128-bit keys and you will be safe: for instance, replace AES-128 with AES-256 and you are done.
Although the currently deployed public key cryptosystems are vulnerable to the Shor's algorithm, the general idea of public key cryptography (asymmetric cryptography) is not, and new public key cryptosystems can be designed based on computational problems that cannot be solved with the Shor's algorithm. Such algorithms are already available and are also currently developed and studied further. They are often referred to as Post-Quantum Cryptography (PQC), but sometimes also called quantum-proof, quantum-safe, or quantum-resistant cryptography. The cryptographic research community has studied PQC already for more than 15 years (the first academic conference on PQC was held in 2006). It is essential to realize that when it comes to implementing PQC algorithms, they are like any other algorithms and can be implemented with existing classical computers.
In December 2016, the American National Institute of Standards and Technology (NIST) announced that it will organize a competition-like process for developing a standard for PQC. NIST aims to standardize PQC algorithms in two categories: key-encapsulation mechanisms and digital signature algorithms. The PQC competition received 69 proposals that fulfilled the initial requirements and that entered Round 1. At the time of writing this blog, the competition has proceeded to Round 3, and 15 algorithms remain in the competition, seven of which are the finalists and the rest are alternatives. After Round 3, NIST will select the first winners from the finalists. They will be included in the forthcoming PQC standard that is expected to be ready within a couple of years.
The key-encapsulation finalists are
The digital signature finalists are
NIST said in the Round 2 status report that Kyber and Saber are its favorite key-encapsulation mechanisms and Dilithium and Falcon are favored for digital signatures. Our view at Xiphera is that the situation has not changed, with the exception of digital signatures where Dilithium and Falcon have become even stronger favorites because Rainbow has been broken. The most promising algorithms (Kyber, Saber, and Dilithium) are based on different variations of the learning with errors problem over rings. The advantages of such cryptosystems over other algorithms in the competition are that they have relatively small key sizes and good performance, and do not really have any obvious weak points like many other candidates (for example, Classic McEliece provides good confidence in its security and fast computations, but suffers from extremely large key sizes).
But, in the end, we must wait for NIST to make the final decision before we have any certainty about the algorithms that will form the basis of the future PQC standard. NIST has stated that the announcement of the winners will be done very soon – by the end of March 2022. Even after that the competition will continue with Round 4 including selected algorithms that may be added into the standard later on.
Also certain European nations (for instance, Germany
and France) have published their own recommendations on PQC. Anyone who designs new systems that require public key cryptography should study also them.
The new PQC algorithms will imply changes into currently used security protocols, and it can be expected that algorithms can be rarely changed in a simple plug-and-play manner. One notable difference, especially when compared with the current ECC-based solutions, is that key sizes will grow regardless of which algorithm is announced as a winner, and for certain algorithms the growth would be significant. Additionally, protocols that currently rely on Diffie-Hellman key exchange will need to change to use a key-encapsulation mechanism for the key exchange (for instance, TLS 1.3). There may also be difference in the speed of computation compared to current highly optimized ECC implementations, but the difference in this respect is probably smaller than what people typically believe. Methods such as Kyber and Saber may be even faster than the current ECC counterparts.
Another aspect to consider is that PQC algorithms have not yet gained a similar level of confidence in their security as RSA and ECC have at the moment. Therefore, it is not completely out of the question that a severe weakness even against classical attacks could be found, and Rainbow already gives us a frightening example. For this reason, many experts (for example, French ANSSI) recommend designing hybrid systems that combine PQC with classical public key cryptography such as ECC. Such hybrid protocols are already under development (see, for example, for TLS).
We at Xiphera are eagerly waiting for the NIST decision and planning to start offering PQC IP cores and solutions to our customers soon after that.
Dr. Matti Tommiska reviews the current status in quantum computing, and specifically its impact on the currently used public-key cryptographic algorithms. The winning algorithms of NIST (National Institute of Standards and Technology) PQC (Post Quantum Cryptography) competition will form the foundation of future public-key cryptographic algorithms and protocols. Since the adoption and finalization of PQC algorithms and protocols will likely take years, the crypto agility of FPGAs has clear advantages over fixed-function silicon.
Find the full recording of the webinar and presentation slides here.
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Einstein famously laboured hard to create the theory of general relativity, but it is less well known that he also helped to launch quantum mechanics, which he didn’t much care for. These two views of the world are the very foundation stones of modern physics – without them we would not have things such as space travel, medical imaging, GPS systems or nuclear energy.
General relativity is unparalleled when it comes to describing the world on a large scale, such as planets and galaxies, while quantum mechanics perfectly describes physics on the smallest scale, such as the atom or even parts of the atom. Uniting the two into a consistent “theory of everything” is the single biggest challenge in physics today – and progress is slow.
The Birth Of Modern Physics
Our knowledge of the universe is based on a sequence of “natural laws”. With time many laws become morphed into new ones as a result of experimental evidence or changing conceptual prejudices. Einstein’s rejection of the concept of universal time was one of the most radical shifts in the history of physics. Its consequences have proved crucial to shaping some of the most profound developments in our understanding of nature.
By fusing the three dimensions of space (height, width and depth) with that of a time direction to construct a “spacetime structure”, a new symmetry of nature could be uncovered. When Einstein later added gravitation to his theories, it led to experimentally verifiable predictions as well as the prediction of gravitational waves and black holes, beyond the natural scope of Newton’s existing law of gravitation.
But Einstein didn’t just work on relativity. A big problem at the time was the fact that Maxwell’s laws, describing electromagnetic phenomena, were unable to explain why faint ultraviolet light falling on metallic electrodes could induce sparks more easily than bright red light. Einstein suggested that this could be understood if the energy in the light wave wasn’t continuously distributed as a wave but rather as a shower of individual “light bullets” (photons – also known as “light quanta”), each with an energy proportional to the colour (frequency) of the light. Many scientists were sceptical of this groundbreaking thought, as so many experiments had already shown that light was a wave.
Millikan proved Einstein right. Nobel foundation/wikipedia, CC BY-SA
One of them was Robert Millikan, who ironically eventually ended up experimentally verifying Einstein’s theory. Millikan also discovered that charged particles known as electrons have wave-like properties. Together with Einstein’s discovery, this pointed to a duality where both matter and light could be described as a particle or as a wave – an idea which led to the development of quantum mechanics by a number of scientists.
This theory has had wide applicability on the smallest of scales, where gravity can often be neglected as it is so weak compared to the other forces affecting particles. Not only has it led to a consistent description of matter and radiation observed in everyday life, it has also made predictions of new particles and processes that are now observed in high-energy accelerator experiments on Earth or cosmic events in space.
To unify the description of matter and radiation quanta with gravitation it became natural to contemplate “gravitational quanta” that carry the force of gravitation. String theory has emerged as a candidate to do this. It states that matter is made up of vibrating extended structures, like tiny strings or membranes, rather than point-like particles. Each type of vibration of these structures corresponds to a particular state of matter.
One type of vibration also corresponds to a gravitational quantum. However, for the resulting quantum description to be consistent it becomes necessary to boost the dimension of spacetime by introducing additional space dimensions that are unobservable to the eye and current technology. To date, there has been no firm experimental confirmation of string theory.
By contrast, in domains where gravitation appears irrelevant, quantum mechanics remains unchallenged, despite describing a very strange world. It states that particles can be in a number of different possible states at once. While the theory can predict a set of probabilities for the particle to be in a particular state, it cannot, in general, predict which probability will actually occur.
In such cases, one must take a large number of observations and then calculate average measurements. Furthermore, such averages depend on what properties are to be measured and when such measurement decisions are made. This peculiar world picture sits uncomfortably alongside Einstein’s world view of causal events and frozen histories in spacetime.
What’s more, according to quantum mechanics, one particle’s state can be correlated with another particle’s state, even if it is in a distant location. Einstein didn’t like this because it seemed to imply that correlations could occur over events that could not be connected by a beam of light, thereby breaking a rule that says nothing can travel faster than the speed of light. He felt that such “spooky action at a distance” was proof for the incompleteness of the theory, although experimental evidence since points to the contrary.
Could the International Space Station be the key to probe the effects of gravity on quantum entanglement? NASA/wikipedia
However, new experiments are underway to see whether gravitational interactions might influence such eerie action in unexpected ways. A research group in Vienna proposes to use the International Space Station to see how gravity might influence this action. A collection of entangled photon pairs will be created on Earth before one member of each pair is sent to the orbiting space station. There, a state known as polarisation will be recorded and compared with the state of its partner on Earth.
It is unclear whether quantum mechanics or general relativity will need either mathematical or conceptual modification in response to future experimental probing. But while the outcome is difficult to predict, Einstein’s influence has been and remains pivotal in this quest.
Robin Tucker, Professor in mathematical physics, Lancaster University
This article was originally published on The Conversation. Read the original article.


Distributed denial-of-service (DDoS) attacks can be a major threat to the availability...
Nowadays, the very abstract ideas underlying the quantum physics are being translated into reality thanks to new technological capabilities in the field of nanotechnology and optical interactions. One of these ideas, the idea of a quantum internet and a quantum computer, will be discussed further in this article. While the subject is very broad, we’ll try to summarize the basic ideas behind these technologies.
Quantum Internet allows to send quantum data (quantum bits or qubits) from one quantum computer to another. The media here is either a fiber optic cable or a free space connection with a clear line of sight between the starting and the destination point of a signal. Classical computers work with conventional bits that can be either zero or one. Quantum mechanics, however, allows qubits to be in a superposition state that can be 1 and 0 at the same time. Therefore, we can encode more information in qubits than in conventional bits. The amount of information that can be stored and processed using qubits is 2n, where n is the number of qubits. So, in two qubit systems, we need four numbers (bits) to determine the state of the system. To define the state of the three qubits system we need 8 numbers. If we have 300 qubits, the equivalent of classical bit information is 2300.
Quantum computer is a computer where the number of operations grows exponentially. However, the improvement is not in the speed of an individual operation but rather a total number of operations to write the result. Therefore, quantum computers are not generally faster, they are faster only for specific types of calculations . We can easily grasp this concept by playing the light switch game provided by D-Wave . The game explains why a quantum computer is faster than a conventional computer in a process of finding the best combination of switches when a number of the switches is large. As stated, “The quantum computer begins with the bits in superposition (the switch can be in both ON and OFF states), ends with them behaving as regular classical bits, and finds the answer along the way”. However, with only 500 switches, there is not enough time in the universe to check all the configurations when conventional processors are used.
So far, only a small number of quantum algorithms have been found.
Here are some of the most famous ones:
Shor’s Algorithm (factorization)
Grover’s Algorithm (quick search in an unordered database)
Deutsch–Jozsa Algorithm (produces an answer; the function is either constant or balanced)
Let’s review the Shor’s algorithm in a bit more detail. It allows to solve any of the two mathematically equivalent problems below:
- Finding the period of a complex periodic function or
- Decomposing a very large number into the prime factors
The second of these tasks is of significant practical importance since it is used in cryptography. When encrypting and decrypting secret messages (public key encryption) large numbers are used for which their factorization is known. It is clear that such numbers are easy to obtain: it is enough to multiply a large number of prime numbers, and we get a very large number for which the factorization is known. The recipient of the encoded secret message can decode it because the decoding procedure uses factorization of a long number, and he/she knows this decomposition.
If a third party could factor this number into the prime factors, he/she would also be able to decode the message. However, this decomposition takes a lot of time. Therefore, from a practical point of view, it is impossible to decode such messages. But if the third party would’ve had a quantum computer, then he/she could decompose long numbers into simple factors quite fast and therefore could easily decipher such messages. The common cryptography method used today would stop working. This is one of the arguments that make the creation of a quantum computer important.
On the other hand, quantum networking provides another secure communication benefit. Quantum Key Distribution (QKD) enables secure communication whose security relays on quantum mechanics. For instance, the spin of an electron can be used as a qubit since it can undergo transitions between the spin-up and spin-down quantum states, represented classically by 0 and 1. In other words, qubits are based on physicals properties of the particles such as electron spins or polarization of photon. However, if we would want to measure the electron’s spin, some of its properties would change. If we were to apply the temperature near the absolute zero (-273 Celsius), the electron would be spin down ↓. If we were to write the information to a qubit we would put the electron into a spin-up state ↑ by hitting it with a pulse of microwaves with specific frequency. We would not know the spin of an electron until we measure it. And when we measure it, the qubit’s physical properties are changed. Therefore, it is also impossible to make exact copies of qubits or to clone it. This is known as a quantum no-cloning theorem. Qubits perfectly suit for secure communication. If Bob and Alice exchange an encryption key using qubits and Eve intercepts communication, both Alice and Bob know that someone messed with qubits as the physicals properties of the qubits changed. Therefore, extracting quantum information without leaving a trace is impossible. The presence of Eve’s eavesdropping communication, can be easily detected.
Nowadays, we can send qubits to short distances over telecommunication fibers up to 200 kilometers. The reason for that is Decoherence – a situation where the system being measured loses its specific quantum properties. In other words, the pure state quickly turns into a mixture when the quantum system interacts with the environment. So, the real challenge in building quantum Internet is to send qubits further than a few hundred kilometers. The single photon sent over a fiber optic cable can be lost. As we know, qubits cannot be copied or amplified so they cannot be resent without a notice. To solve this issue, the box called a quantum repeater is placed in the middle of the communication line and the pair of photons is exchanged between the repeater and the quantum computer on the left side of the line. Similarly, another pair of photons is exchanged between the repeater and a quantum computer located to the right of the communication line. Quantum repeaters are crucial for entanglement over long distances using fiber optic cables. The vision is to build a long-range quantum internet that will operate in parallel to the Internet we know today.
We have already mentioned, that transmission of quantum signals over long distances is prevented by fiber attenuation and the no-cloning theorem. Therefore, one of the realistic scenarios is that the future Quantum Internet will consist of a global network of quantum repeaters that are developed and used in order to extend the range of communication. However, there is also another approach to this problem which is based on the deployment of satellite technology. China launched world’s first quantum communication satellite Miciusin 2016, and has since been busy testing and extending the limitations of sending entangled photons from space to ground stations on Earth and back again . Chinese and European researchers have tested the system by creating secure video conference between Europe and China.
There are certain issues associated with quantum computing besides decoherence, such as the search for new algorithms as well as new methods of error correction. All of these problems however can be described in one phrase – scalability issues.
Quantum computers are the “holy grail” of modern physics and informatics. The idea of a quantum computer and a quantum network looks unrealistic at first. A regular classical computer was probably perceived the same way at the time of Charles Babbage, the invention of which happened only a hundred years later. QCs on two or three qubits already exist, but they require the use of high technologies (pure substances, precise implantation of individual atoms, a highly accurate measurement system, etc.). However, as mentioned earlier, the main challenge is not the technological one but the fundamental one of scalability.
It is unlikely that quantum computers will replace the classical computers in the near future. We can only speculate that the QCs would be put into clouds to offer unique services whereas personal computers would transmit or access the quantum-encrypted information through the cloud-based QCs.
Hopefully, the scientific and technical progress of our time is fast enough, and we will not have to wait too long for quantum computing to become a common reality.


As data travels through different networks, there is an increased possibility of attacks. AES is the encryption standard used by organizations worldwide to secure sensitive data. AES was published when the need for a better encryption model became apparent. While Data Encryption Standard (DES) was used for around 20 years, AES came as an alternative to DES when it started becoming vulnerable to brute force attacks.
AES comes in 128, 192, and 256 bits. This article will help you understand the AES-128 in detail.
AES-128 conceals plaintext data using an AES key length of 128 bits. AES-128 encrypts data using 10 transformation rouns and is best suited for protecting secret government information as recommended by the National Security Agency (NSA). The block size of the data encrypted using AES is always 128 bits. 128-bits is the least secure among other variants of the AES algorithm. However, this doesn’t mean that AES-128 is crackable. Since other variants such as 192-bits and 256-bits use more rounds for transformation, AES-128 is comparatively less secure.
The steps involved in AES-128 encryption include the substitution of data using a substitution table, shifting rows, mixing columns, and insertion of another round key.
How Secure is AES-128 Against Brute Force Attacks?
AES processes 128 bits of input data at a time. Based on the substitution-permutation network, AES is a symmetric key. AES performs all its computations on bytes which means it treats the 128 bits of a block as 16 bytes. The bytes are processed as a matrix with 16 bytes organized into four columns and four rows. DES with a key size of 56 bits has been cracked using brute force attacks in the past. AES-128 is a 128-bit symmetric key that is computationally secure against brute force attacks.
If you ask how long will it take to crack 128-bit encryption using a brute force attack, the answer would be 1 billion years. A machine that can crack a DES key in a second would take 149 trillion years to crack a 128-bit AES key. Hence, it is safe to say that AES-128 encryption is safe against brute-force attacks. AES has never been cracked yet and it would take large amounts of computational power to crack this key. Governmental organizations and businesses trust the AES for securing sensitive information.
What’s the difference between AES-128 and AES-256?
AES is considered safe against brute force attacks. Key size is a critical factor in determining whether the algorithm can be cracked. The key size should be large enough to resist attacks from modern computers with large computational power. Understandably, a 256-bit is more difficult to crack due to its key length. However, even cracking a 128-bit key would need quantum computing to generate the necessary brute force.
One of the major differences between AES-128 and AES-256 is that the latter takes longer to execute and requires more computational power. Hence, wherever power and latency are a concern, AES-128 encryption is recommended.
Regardless of whether AES-128 or AES-256 is used, the surrounding infrastructure should be strong and secure to keep hackers from breaking into the system. The software implemented should be secure and perform functions as the user wants it to. Every organization should have strict guidelines for data handling and storage. Users must follow the security best practices irrespective of what encryption model is being implemented.
Choosing between AES-128 and AES-256
As stated earlier, AES-128 uses a 128-bit key length to encrypt and decrypt a block of message whereas AES-256 uses a 256-bit key length to encrypt and decrypt a block of message. Both encryption models have their own pros and cons.
AES-128 has greater speed. It is comparatively more efficient and resistant to full attacks. AES-128 is suited to protect secret information. AES-256 on the other hand may be a bit slower and take longer to execute. However, it is used to protect the top-secret information of the government. AES-256 can resist brute force attacks but may not safeguard against related-key attacks.
AES is the modern encryption standard capable of resisting attacks in the current threat landscape. Choosing AES-128 or AES-256 depends on each organization’s individual security needs. AES-18 is fast and resource-efficient and provides enough security against cyber attacks. But organizations that deal with highly sensitive information such as the defense sector should go with AES-256 as the longer key size provides extra protection against attacks.
A 128-bit level of encryption has 2128 possible key combinations. AES is by far the most advanced encryption trusted by organizations worldwide. AES-128 is strong enough to meet future security needs. AES is used in self-encrypting disk drives, database encryption, and storage encryption. AES can be safely implemented in firmware, hardware, and applications that need low latency and high throughput.
In the present day, AES is widely used in software and hardware. AES assures security only if the implementation is right. Keys should be stored properly as hackers can easily misuse data if they get their hands on the keys. Key management is critical to ensure AES provides a strong defense against attacks. AES remains the best choice for securing communications as it has more key length options.
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A new method using conventional computing can reduce simulation time from 600 million years to months, challenging a claim of ‘quantum advantage’.
Achieving ‘quantum advantage’ – where a quantum computer can achieve something even the world’s fastest conventional supercomputers can’t on a reasonable timescale – is an important landmark on the journey toward creating a useful quantum computer.
Quantum computing is of course the holy grail, but it is often easy to lose sight of the importance of the computational resources we currently have that can help us along the way. Dr Raj Patel
Researchers at the University of Bristol, Imperial College London, the University of Oxford, and Hewlett-Packard Enterprises are keeping pace with quantum advantage by developing new methods that can reduce simulation time on conventional computers by a speedup factor of around one billion.
Quantum computers promise exponential speedups for certain problems, with potential applications in areas from drug discovery to new materials for batteries. But quantum computing is still in its early stages, so these are long-term goals.
The new research, published today in the journal Science Advances, challenges a previous claim of quantum advantage by improving a method of conventional computing, vastly speeding it up.
Claiming quantum advantage
The study follows an experimental paper from the University of Science and Technology of China (USTC) that was the first to claim quantum advantage using photons – particles of light.
In USTC's experiment, they generated a large and highly complex quantum state of light and measured it using single-photon detectors in a protocol called ‘Gaussian Boson Sampling’ (GBS). Their paper claimed that the experiment, performed in 200 seconds, would take 600 million years to simulate on the world's largest supercomputer.
The new study reveals that updated methods of simulating GBS can reduce the predicted simulation time of 600 million years down to just a few months, a speedup factor of around one billion.
Joint first author Dr Bryn Bell, previously of the Department of Physics at Imperial and now Senior Quantum Engineer at Oxford Quantum Circuits, said: “As researchers develop larger scale experiments, they will look to make claims of quantum advantage relative to classical simulations. Our results will provide an essential point of comparison by which to establish the computational power of future GBS experiments.”
The value of current computational resources
Co-author Dr Raj Patel, from the Department of Physics at Imperial and the University of Oxford said: “Our work with the University of Bristol and Hewlett-Packard Enterprises emphasises the need to continue developing simulation methods that run on ‘classical’ hardware.
"Quantum computing is of course the holy grail, but it is often easy to lose sight of the importance of the computational resources we currently have that can help us along the way.
“Using these resources to find the boundary at which quantum advantage can be obtained is not only of academic interest but is crucial in instilling confidence in potential stakeholders in emerging quantum technologies.”
The team’s methods do not exploit any errors in the experiment and so one next step for the research is to combine their new methods with techniques that exploit the imperfections of the real-world experiment. This would further speed up simulation time and build a greater understanding of which areas require improvements.
Joint first author Jake Bulmer, a PhD student at the University of Bristol, said: “The USTC estimate used the best-known simulation methods known at the time, but we were confident significant improvements could be made. By asking ourselves, what is it about this experiment which makes it complex, we could uncover understanding for how to simulate it in the most efficient way.
“In essence, our methods reveal which parts of GBS experiments are important and which are not when it comes to designing new generations of devices. For example, we show that if the photon detectors are improved, this could substantially increase the complexity of the experiment.
“These simulated experiments represent a tremendous achievement of physics and engineering. As a researcher, it is truly exciting to contribute to the understanding of where the computational complexity of these experiments arises. We were pretty thrilled with the magnitude of the improvements we achieved - it is not often that you can claim to find a one-billion-fold improvement!”
‘The boundary for quantum advantage in Gaussian boson sampling’ by Jacob F. F. Bulmer et al. is published in Science Advances.
Based on a press release by the University of Bristol.
Article text (excluding photos or graphics) © Imperial College London.
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