Cryptography is the backbone of our current digital society, but how did it become so important? Interestingly, the systematic study of cryptography as a science (and perhaps as an art) started only during the past 100 years.
The word cryptography is derived from the Greek krypto and graphein, which mean hide and writing. The first type of cryptography was simple writing, since the majority of people could not read (New World, 2007). Later, most of the great civilizations used some kind of cryptography to transfer important private information. The earliest form of cryptography was a cipher (a cipher is an algorithm used for encryption or decryption). Ciphers had the problem of being easily broken using the frequency of the letters, and once a generalized way of breaking them was found they became obsolete.
Middle ages to today
The next big advance came in the 1600s when the first cryptographic key was recorded, which caused a big shift in the space, moving the importance from hiding the system to hiding the key. The system could be public, but one could still not read the message without the key. That overcame the problem of a system as a whole becoming obsolete with the discovery of its mechanism.
Then, during 19th Century the first use of a rotor for encryption was recorded. In the 20th Century the invention of the Enigma machine (used by the German military during WWII) was a technical milestone, being one of the hardest ciphers to break. However, that too was eventually broken by Poland, and British cryptographers designed a means to obtain the daily key.
After the war, cryptography found its way into commercial applications, with IBM being the first company to systematically develop a crypto-group and what ended up being the first U.S. standard for encryption. The standard, though, was short-lived, since it was also broken by a simple but very powerful method called a brute-force attack. Brute-force involves simply trying all the possible combinations in a very computationally intensive process. That is also why advances in computing power are followed by increases in the complexity of the private keys.
Cryptography has been a continuous game of chase between the complexity of the cryptographic keys and the computing power available. In principle, any key is vulnerable to a brute-force attack; the more complex the key the more time consuming such an attack is.
The importance of cryptography in the digital age
Advances in technology and computing power have enabled people to move more and more of their data to the digital sphere. Moving data through any digital means—aside from the obvious advantage it brings to speed, accessibility, and convenience—comes with the mirroring disadvantage of being harder to protect.
The need to protect digital data from being used for unlawful purposes is being tackled by cryptography. However, as with all rights, there are competing interests. Law enforcement has a legitimate right to intercept communications in certain circumstances. Balancing these rights requires a balance known as the tightrope between security and privacy.
The importance of cryptography can be summarized by the fact that it is the only tool the user has in the digital world to protect their private data. And as we move more and more into the digital world, by association, cryptography is becoming more and more important.
The state of cryptography today
Today the need to communicate with parties we cannot necessarily trust, has given rise to “public-key cryptography” or “asymmetric cryptography.” This kind of cryptography relies on public keys that the sender uses to encrypt the message and private keys which the receiver has and uses to decipher the message. This process is one-way, meaning that no one else can decipher the message. Even these state-of-the-art methods are still breakable. If nothing else, an algorithm can be broken by a brute-force attack that cycles through every possible key. Therefore, the goal of present-day cryptography is to create algorithms that make it computationally infeasible for an attacker to recover the private key.
What about privacy?
Even though state-of-the-art cryptographic protocols are virtually unbreakable because of required computing time, companies and individuals are ever in search of more ways to transact more privately. Recently, with advances in computing power and cryptography, trust has become a new target for individuals and organizations concerned with privacy. Cryptographers have thought that if it is possible to encrypt and effectively hide the data from people who don’t have to see it, perhaps there is a way to still transact with them without showing the data. And sure enough, during the 1980s tools such as zero-knowledge proofs and calculations on encrypted data were discovered. By applying mathematical transformations to the underlying data, these tools enable people to interact with and validate encrypted data, effectively creating another revolution in the field. Now the data exchange can be private, even between parties that transact directly.
Increased efficiency for high-demand protocols
In 2012 Project Pinocchio from IBM and Microsoft found a way to reduce the computing needs of a zero-knowledge proof by 20x and for zero-knowledge verification by more than 50x, making it efficient enough for practical uses. It now can be used to hide the data between two parties and still allow them to transact, not only theoretically, but fast enough to have private and commercial applications. This breakthrough opened new possibilities to businesses and researchers, who started wondering what other applications are within reach and what other technological possibilities exist.
That same curiosity is what drove us at decentriq to explore these technologies in the first place. Our team develops novel implementations for cutting-edge and privacy-preserving technologies. We explore applications such as:
- Secure and private online voting
- Augmented privacy for exchanges, enabling them to not have to reveal their whole order book
- A bulletproof way for anyone to provide a proof of cryptographic assets without ever revealing the funds available in one’s account
- A marketplace for alternative data providers and buyers that enables the business to try the data before deciding to buy it, while keeping the data hidden
- Making possible a demonstration of the predictive power of a model on new data without disclosing the model or the data
All these applications are made possible by recent and ongoing research, both by decentriq and by third-party open-source projects fueled by demand for increased security and privacy in individual and commercial datasets.
What does the future of cryptography hold?
These cutting-edge discoveries and advancements in cryptography are cultivating an exciting future for the field. What appears to be the biggest change on the horizon is quantum computing. Quantum computing, using the properties of the superpositioned particles, is able to exponentially increase the computing power available to us. That means the cryptographic transformations that today are inefficient to run on a silicon chip can be run efficiently on a quantum chip, potentially rendering today’s encryption obsolete.
Today, we encrypt data as it travels over the internet and when it is at rest on a storage device. But we have to decrypt data to use or analyze it, creating a potential security vulnerability. Homomorphic encryption is a new idea that solves that problem, allowing users to process data without decrypting it. With homomorphic encryption, we process encrypted data and produce encrypted results. And while this is not a novel idea, new breakthroughs that vastly improved performance brought the possibility of efficient encrypted data processing back to the forefront.
Thus, the chase continues. The advances in quantum computing have given rise to quantum encryption, which uses the properties of quantum particles to ensure unbreakable encryption. There are already several projects working on quantum encryption and how it can be implemented. Even though quantum computing at scale may be many years away, we at decentriq follow the technology closely to make sure we are ahead of the curve for our customers when the time comes. Nevertheless, until then, we apply our cryptographic skills to the betterment of cutting-edge protocols, making them more efficient, user-friendly, and wider known to everyone who could benefit from them. We believe that in a world where the most valuable asset is information, it is worth exploring novel technological uses for confidential computing to protect it.


Only a few decades ago quantum technology was purely a theoretical thing. Something that scientists dreamed of. But now, even though this is still an emerging field of physics and engineering, we are very close to breaking through a great discovery.
Just in October 2019 Google “performed a test computation in just 200 seconds that would have taken the best-known algorithms in the most powerful supercomputers thousands of years to accomplish.”
The effects of quantum computing are promising in various areas because mathematical operations can be done considerably faster than the most powerful supercomputers to date can. This is achieved by relying on the principles of quantum physics.
While this might seem like something arcane or even impossible for some people, quantum-based technology has been in use for a while now. Take MRI machines, for example, which creates images based on the spinning of atoms inside our body.
Or some more common technology, like one that can fit in your hand and could tell you where you are at any given time, GPSs. Global Positioning Systems are based on quantum theory.
Among all the quantum technology, the one that causes more controversy is the quantum computer. Its immense computing power can be used to speed up research in medical fields, test more efficient building materials, have better control over certain processes, create algorithms that solve complex problems.
If you think of some of the listed benefits the impact of quantum computing does not seem all that bad. So, why the controversy? What are the negative effects of quantum computing?
To understand this better we have to first answer one question.
What is quantum computing?
The fact that there are quantum computers that can already operate 1 trillion times faster than what a supercomputer can, has led people to seriously question the cybersecurity implications of quantum computing.
Traditional computers store data in bits. Based on a binary system in which values are 1 an 0 which can translate to 2 states of information, positive and negative respectively. This binary system in which traditional computing is based is also the reason why Megabytes are composed of 1,024 Kilobytes, instead of just 1000 as the name implies.
Although current computing is not obsolete, the binary system has some limitations when it comes to really long and complex operations. Like the ones in which thousands of variables have an impact.
On the other hand, we have quantum-based computers that use qubits instead of bits. The interesting thing about these qubits is that they do not only represent a 1 or a 0 value, but they can also exist as both values at the same time. This quantum property is called superposition, the ability to be positive and negative at the same time.
One of the ways that a qubit can be created is by using superconductivity to maintain a quantum state of the particle. To achieve this, the superconducting qubits must be kept extremely cold, even colder than the vacuum of space. In fact, an absolute 0 cold, or as close as possible.
This is the lowest limit of temperature according to the laws of thermodynamics. 0° Kelvin is about -273.15 C°. At this temperature, the matter has no heat or vibration remaining in it and it only retains its quantum mechanical properties.
Although interesting, that might not seem like very useful information for the casual observer. The most important piece of information that you need to understand quantum computing is that it leverages the quantum properties of particles to exponentially increase processing power.
For instance, Google’s Sycamore Quantum Computer completed a complex computation in 200 seconds. A calculation that would take even the most powerful supercomputers an estimate of 10,000 years.
Although that calculation does not have any real use outside the world of quantum computing it is still pretty impressive. However, that same capability of solving complex problems becomes a menace when it is faced with mathematical problems that should not be solved.
This is the case with cybersecurity.
Although Cybersecurity is composed of various components, including best practices, encryption is fundamental to maintain information unreadable for unwanted eyes.
Current encryption is based on mathematical formulas that transform this clear data into an encrypted message that is supposed to be secure. This way you can transmit or store information and no one without the proper digital key will be able to access it.
Breaking an encryption key is a mathematically daunting task. To the point of being considered impossible to achieve by today’s computing power.
The most straightforward way to break an encryption code is to try all the possible keys until you get the right one. It would seem simple, but imagine this:
A simple 64 bits encryption has 1,800,000,000,000,000,000 possible combinations. A 128 bits encryption code has more than 300 undecillion possible solutions. Even the world’s fastest supercomputer would take an estimate of a trillion years to find that key.
Up to a certain extent, conventional computers can do this. In July 2002 a group announced that it had uncovered a symmetric 64-bit key. However, it took 300,000 people and more than four and a half years of work to achieve this.
A quantum computing method called Grover’s algorithm, however, speeds up the process, turning that 128-bit key into the quantum-computational equivalent of a 64-bit key. The defense is straightforward, though: Make keys longer. A 256-bit key, for example, has the same security against a quantum attack as a 128-bit key has against a conventional attack.
Under these terms, a quantum computer that can operate trillions of times faster than the fastest supercomputer becomes a game-changer.
Encryption is vital to cybersecurity and privacy, at a personal level, at a corporate level and even at a government level. Although the current most secure encryption methods (256 bits) will not become useless against quantum computing, it’s security will be considerably weakened.
The implications of quantum computing in cybersecurity are tangible and it puts a lot more than just a text message at risk. We can only expect that as this technology evolves, encryption methods will evolve as well.


Physicists at MIT and elsewhere have observed evidence of Majorana fermions — particles that are theorized to also be their own antiparticle — on the surface of a common metal: gold. This is the first sighting of Majorana fermions on a platform that can potentially be scaled up. The results, published in the Proceedings of the National Academy of Sciences, are a major step toward isolating the particles as stable, error-proof qubits for quantum computing.
In particle physics, fermions are a class of elementary particles that includes electrons, protons, neutrons, and quarks, all of which make up the building blocks of matter. For the most part, these particles are considered Dirac fermions, after the English physicist Paul Dirac, who first predicted that all fermionic fundamental particles should have a counterpart, somewhere in the universe, in the form of an antiparticle — essentially, an identical twin of opposite charge.
In 1937, the Italian theoretical physicist Ettore Majorana extended Dirac’s theory, predicting that among fermions, there should be some particles, since named Majorana fermions, that are indistinguishable from their antiparticles. Mysteriously, the physicist disappeared during a ferry trip off the Italian coast just a year after making his prediction. Scientists have been looking for Majorana’s enigmatic particle ever since. It has been suggested, but not proven, that the neutrino may be a Majorana particle. On the other hand, theorists have predicted that Majorana fermions may also exist in solids under special conditions.
Now the MIT-led team has observed evidence of Majorana fermions in a material system they designed and fabricated, which consists of nanowires of gold grown atop a superconducting material, vanadium, and dotted with small, ferromagnetic “islands” of europium sulfide. When the researchers scanned the surface near the islands, they saw signature signal spikes near zero energy on the very top surface of gold that, according to theory, should only be generated by pairs of Majorana fermions.
“Majorana ferminons are these exotic things, that have long been a dream to see, and we now see them in a very simple material — gold,” says Jagadeesh Moodera, a senior research scientist in MIT’s Department of Physics. “We’ve shown they are there, and stable, and easily scalable.”
“The next push will be to take these objects and make them into qubits, which would be huge progress toward practical quantum computing,” adds co-author Patrick Lee, the William and Emma Rogers Professor of Physics at MIT.
Lee and Moodera’s coauthors include former MIT postdoc and first author Sujit Manna (currently on the faculty at the Indian Institute of Technology at Delhi), and former MIT postdoc Peng Wei of University of California at Riverside, along with Yingming Xie and Kam Tuen Law of the Hong Kong University of Science and Technology.
If they could be harnessed, Majorana fermions would be ideal as qubits, or individual computational units for quantum computers. The idea is that a qubit would be made of combinations of pairs of Majorana fermions, each of which would be separated from its partner. If noise errors affect one member of the pair, the other should remain unaffected, thereby preserving the integrity of the qubit and enabling it to correctly carry out a computation.
Scientists have looked for Majorana fermions in semiconductors, the materials used in conventional, transistor-based computing. In their experiments, researchers have combined semiconductors with superconductors — materials through which electrons can travel without resistance. This combination imparts superconductive properties to conventional semiconductors, which physicists believe should induce particles in the semiconductor to split , forming the pair of Majorana fermions.
“There are several material platforms where people believe they’ve seen Majorana particles,” Lee says. “The evidence is stronger and stronger, but it’s still not 100 percent proven.”
What’s more, the semiconductor-based setups to date have been difficult to scale up to produce the thousands or millions of qubits needed for a practical quantum computer, because they require growing very precise crystals of semiconducting material and it is very challenging to turn these into high-quality superconductors.
About a decade ago, Lee, working with his graduate student Andrew Potter, had an idea: Perhaps physicists might be able to observe Majorana fermions in metal, a material that readily becomes superconductive in proximity with a superconductor. Scientists routinely make metals, including gold, into superconductors. Lee’s idea was to see if gold’s surface state — its very top layer of atoms — could be made to be superconductive. If this could be achieved, then gold could serve as a clean, atomically precise system in which researchers could observe Majorana fermions.
Lee proposed, based on Moodera’s prior work with ferromagnetic insulators, that if it were placed atop a superconductive surface state of gold, then researchers should have a good chance of clearly seeing signatures of Majorana fermions.
“When we first proposed this, I couldn’t convince a lot of experimentalists to try it, because the technology was daunting,” says Lee who eventually partnered with Moodera’s experimental group to to secure crucial funding from the Templeton Foundation to realize the design. “Jagadeesh and Peng really had to reinvent the wheel. It was extremely courageous to jump into this, because it’s really a high-risk, but we think a high-payoff, thing.”
Over the last few years, the researchers have characterized gold’s surface state and proved that it could work as a platform for observing Majorana fermions, after which the group began fabricating the setup that Lee envisioned years ago.
They first grew a sheet of superconducting vanadium, on top of which they overlaid nanowires of gold layer, measuring about 4 nanometers thick. They tested the conductivity of gold’s very top layer, and found that it did, in fact, become superconductive in proximity with the vanadium. They then deposited over the gold nanowires “islands” of europium sulfide, a ferromagnetic material that is able to provide the needed internal magnetic fields to create the Majorana fermions.
The team then applied a tiny voltage and used scanning tunneling microscopy, a specialized technique that enabled the researchers to scan the energy spectrum around each island on gold’s surface.
Moodera and his colleagues then looked for a very specific energy signature that only Majorana fermions should produce, if they exist. In any superconducting material, electrons travel through at certain energy ranges. There is however a desert, or “energy gap” where there should be no electrons. If there is a spike inside this gap, it is very likely a signature of Majorana fermions.
Looking through their data, the researchers observed spikes inside this energy gap on opposite ends of several islands along the the direction of the magnetic field, that were clear signatures of pairs of Majorana fermions.
“We only see this spike on opposite sides of the island, as theory predicted,” Moodera says. “Anywhere else, you don’t see it.”
“In my talks, I like to say that we are finding Majorana, on an island in a sea of gold,” Lee adds.
Moodera says the team’s setup, requiring just three layers — gold sandwiched between a ferromagnet and a superconductor — is an “easily achievable, stable system” that should also be economically scalable compared to conventional, semiconductor-based approaches to generate qubits.
“Seeing a pair of Majorana fermions is an important step toward making a qubit,” Wei says. “The next step is to make a qubit from these particles, and we now have some ideas for how to go about doing this.”
The study was published in Massachusetts Institute of Technology


Storing quantum bits of information, or qubits, is a lot harder than storing ordinary binary digits. It’s not simply ones or zeroes, but the whole range of subtle quantum superpositions between them. Electrons can easily slide out of those states if they’re not stored in the right materials, which is why electrical engineers at Princeton are working with a UK manufacturer to create a better storage material — synthetic diamonds — from scratch. They published an account of their success on Thursday in Science.
For decades, physicists, materials engineers, and others have been trying to achieve the conceptual promise of quantum-encrypted communications because the data transferred in that process is theoretically immune to covert surveillance. Any attempt to observe that data between parties — à la the Heisenberg Uncertainty Principle — would fundamentally alter that information, quickly revealing that it was compromised. The problem has been storing and preserving qubits and then converting them to fiber optic-ready photons, and using diamonds appears to be the route toward achieving both. But not just any diamond will do, which is why Princeton’s team has been hard at work creating a synthetic one, as they describe in their paper.
“The properties that we’re targeting are what’s relevant for quantum networks,” electrical engineer Nathalie de Leon tells Inverse. At Princeton, where de Leon is an assistant professor, her team’s focus is essentially inventing quantum hardware. “It’s applications where you want something that has a long storage time, and then also has a good interface with photons so that you can send light over very long distances.”
Photonic interactions matter a lot for high-speed international communications because all of the information traveling along fiber optic cables moves through our global infrastructure as discrete photons — cruising at 69 percent of the speed of light. (Nice.)
“That puts a lot of constraints on the optical characteristics,” de Leon says. “As one example, it’s really important that the color be stable. If the color of the photon is jumping around over time, then that’s really bad for these protocols.”
Right now, de Leon’s group is trying to craft a version of these synthetic diamonds that can convert to the standard 1,550-nanometer wavelength on which photons now traverse fiber optic cables. Currently, her team’s synthetic diamonds support 946-nanometer photon wavelengths. (Photon “color” is a bit of a euphemism here since both of these wavelengths are shades of infrared outside the visible spectrum.)
The hurdle that her team just succeeded in crossing is storing those qubits in crystalline quantum repeaters, similar to the repeaters that are currently used to prevent signal loss and degradation in today’s fiber-optic communications. The critical step in this process was producing synthetic diamonds with as little unwanted impurities as possible (nitrogen, mainly) and more of the impurities they actually did want (silicon and boron).
“Nitrogen turns out to be the predominant defect that you get in these diamonds,” de Leon says. Her group’s partners at the British diamond maker Element Six had to create above-average vacuum conditions since even ordinary vacuums can leave enough nitrogen in the chamber to contaminate the artificially-made crystals. Because nitrogen has one more free electron than carbon, nitrogen impurities disturb the unique electrical makeup that the researchers are hoping for.
Other small defects can undermine the qubit-storing potential of these diamonds, too. The goal is to have pairs of atom-sized vacancies in the crystal framework alongside a substituted silicon atom where a single carbon used to be, but sometimes those pairs can bunch up together in “vacancy clusters” that start to redistribute their electrons in annoying, counterproductive ways. Sometimes polishing and etching damage on the surface of the diamond can also cause a domino effect, messing with this pattern of electrons, too. This is where adding boron — which has one less free electron than carbon — can help.
“What we had to do,” de Leon says, “is both start with this ultra-high purity diamond and then grow in some boron to basically soak up any of the extra electrons that we couldn’t control. Then there was a lot of materials processing — boring stuff like thermal annealing and repairing the surface at the end to make sure that we still get rid of a lot of these other types of defects that give you extra charges.”
Mastering both of these challenges, many in the field suspect, are the keys to fully functional and nearly impossible to crack quantum encryption.
Before the dawn of synthetic diamonds only a few years ago, researchers in the field of quantum optics had to rely on natural diamonds to do their work — one specific diamond, in particular.
According to de Leon, everyone in the field of quantum optics had to rely on a single, naturally-made diamond from Russia that just happened to have the right percentage of boron, nitrogen, and other impurities to make their research possible. Fragments of the diamond were cleaved off and distributed to research groups across the world.
“Many of the groups had their own little piece of the ‘magic’ Russian diamond,” as de Leon told Princeton’s in-house news service in 2016. “At Harvard, we called ours ‘Magic Alice’ and ‘Magic Bob.’”
So, TL;DR, Western scientists are getting better at manufacturing their own magical quantum computing diamonds instead of depending on slivers of Russia’s magical quantum computing diamond. This is a factual sentence that sounds ridiculous. Classic 2018.


Quantum computers are largely hypothetical devices that could perform some calculations much more rapidly than conventional computers can. Instead of the bits of classical computation, which can represent 0 or 1, quantum computers consist of quantum bits, or qubits, which can, in some sense, represent 0 and 1 simultaneously.
Although quantum systems with as many as 12 qubits have been demonstrated in the lab, building quantum computers complex enough to perform useful computations will require miniaturizing qubit technology, much the way the miniaturization of transistors enabled modern computers.
Trapped ions are probably the most widely studied qubit technology, but they’ve historically required a large and complex hardware apparatus. In today’s Nature Nanotechnology, researchers from MIT and MIT Lincoln Laboratory report an important step toward practical quantum computers, with a paper describing a prototype chip that can trap ions in an electric field and, with built-in optics, direct laser light toward each of them.
“If you look at the traditional assembly, it’s a barrel that has a vacuum inside it, and inside that is this cage that’s trapping the ions. Then there’s basically an entire laboratory of external optics that are guiding the laser beams to the assembly of ions,” says Rajeev Ram, an MIT professor of electrical engineering and one of the senior authors on the paper. “Our vision is to take that external laboratory and miniaturize much of it onto a chip.”
The Quantum Information and Integrated Nanosystems group at Lincoln Laboratory was one of several research groups already working to develop simpler, smaller ion traps known as surface traps. A standard ion trap looks like a tiny cage, whose bars are electrodes that produce an electric field. Ions line up in the center of the cage, parallel to the bars. A surface trap, by contrast, is a chip with electrodes embedded in its surface. The ions hover 50 micrometers above the electrodes.
Cage traps are intrinsically limited in size, but surface traps could, in principle, be extended indefinitely. With current technology, they would still have to be held in a vacuum chamber, but they would allow many more qubits to be crammed inside.
“We believe that surface traps are a key technology to enable these systems to scale to the very large number of ions that will be required for large-scale quantum computing,” says Jeremy Sage, who together with John Chiaverini leads Lincoln Laboratory’s trapped-ion quantum-information-processing project. “These cage traps work very well, but they really only work for maybe 10 to 20 ions, and they basically max out around there.”
Performing a quantum computation, however, requires precisely controlling the energy state of every qubit independently, and trapped-ion qubits are controlled with laser beams. In a surface trap, the ions are only about 5 micrometers apart. Hitting a single ion with an external laser, without affecting its neighbors, is incredibly difficult; only a few groups had previously attempted it, and their techniques weren’t practical for large-scale systems.
That’s where Ram’s group comes in. Ram and Karan Mehta, an MIT graduate student in electrical engineering and first author on the new paper, designed and built a suite of on-chip optical components that can channel laser light toward individual ions. Sage, Chiaverini, and their Lincoln Lab colleagues Colin Bruzewicz and Robert McConnell retooled their surface trap to accommodate the integrated optics without compromising its performance. Together, both groups designed and executed the experiments to test the new system.
“Typically, for surface electrode traps, the laser beam is coming from an optical table and entering this system, so there’s always this concern about the beam vibrating or moving,” Ram says. “With photonic integration, you’re not concerned about beam-pointing stability, because it’s all on the same chip that the electrodes are on. So now everything is registered against each other, and it’s stable.”
The researchers’ new chip is built on a quartz substrate. On top of the quartz is a network of silicon nitride “waveguides,” which route laser light across the chip. Above the waveguides is a layer of glass, and on top of that are niobium electrodes with tiny holes in them to allow light to pass through. Beneath the holes in the electrodes, the waveguides break into a series of sequential ridges, a “diffraction grating” precisely engineered to direct light up through the holes and concentrate it into a beam narrow enough that it will target a single ion, 50 micrometers above the surface of the chip.
With the prototype chip, the researchers were evaluating the performance of the diffraction gratings and the ion traps, but there was no mechanism for varying the amount of light delivered to each ion. In ongoing work, the researchers are investigating the addition of light modulators to the diffraction gratings, so that different qubits can simultaneously receive light of different, time-varying intensities. That would make programming the qubits more efficient, which is vital in a practical quantum information system, since the number of quantum operations the system can perform is limited by the “coherence time” of the qubits.
“As far as I know, this is the first serious attempt to integrate optical waveguides in the same chip as an ion trap, which is a very significant step forward on the path to scaling up ion-trap quantum information processors [QIP] to the sort of size which will ultimately contain the number of qubits necessary for doing useful QIP,” says David Lucas, a professor of physics at Oxford University. “Trapped-ion qubits are well-known for being able to achieve record-breaking coherence times and very precise operations on small numbers of qubits. Arguably, the most important area in which progress needs to be made is technologies which will enable the systems to be scaled up to larger numbers of qubits. This is exactly the need being addressed so impressively by this research.”
“Of course, it's important to appreciate that this is a first demonstration,” Lucas adds. “But there are good prospects for believing that the technology can be improved substantially. As a first step, it's a wonderful piece of work.”


Blog: Quantum Algorithms
In previous articles we introduced the main topics related to Quantum Computing ( https://firstname.lastname@example.org/quantum-computing-7662907581e5) in order to have a basic idea of what is it and the definitions we need to know so that one is capable of understanding the entire work.
Quantum computing algorithms can be divided into three groups: algorithms based on the quantum version of the Fourier transform, search algorithms and quantum simulations. In this section some well-known and relevant algorithms of quantum computing will be introduced, we will proceed to explain their purpose and their logic and, in turn, we will analyze in detail their respective circuits .
The algorithms to analyze are the following:
1. Deutsch Algorithm
2. Grover Algorithm
Deutsch’s algorithm combines what is known as quantum parallelism with another quantum phenomenon called interference. The problem that this algorithm tries to solve is how to determine if the function 𝑓(𝑥) of binary variable and binary image is constant or alternates with a minimum number of calls to the function 𝑓(𝑥). It is shown that classically two calls are needed while in the quantum algorithm is enough with one. It is the first quantum algorithm that showed quantum superiority.
The circuit of this algorithm is as follows:
In figure 1 one can see that we have two qubits to which a Hadamard gate is applied. This gateway is to prepare the qubit in a superposition. In this case we have as input
with the help of the Hadamard gates we put the qubits into the following superposition states
In figure 1, we have the Uf gate that performs the following action
U stands for unitary and for practical purposes we will treat it as a black box. This gate affects the state
by adding the following term
Applied, then, to (3) we obtain
Finally, we apply another Hadamard gate to the first qubit, remaining (7) as follows
The established conditions tell us that if
is 0 and 1 in other cases. In order to keep things easy to read, we rewrite (8)
In this way, by measuring the first qubit, we can determine 𝑓(0)⊕𝑓(1). That is, the system allows us to know a global property of the function in a single evaluation. With a “classic” device we would have taken at least two evaluations. It should be noted that if we were in classical computing, we could not obtain information from the two solutions at the same time. However, in quantum computing solutions can interfere with each other to give us a global solution, as we got.
Finally we are going to analyze Grover’s algorithm. We will do it without introducing too much into the circuit, unlike the other example. This algorithm belongs to a special class of quantum algorithms called quantum search algorithms.
This type of algorithm attempts to solve the following problem: given a search space of size 𝑁, and without prior knowledge of what it contains, we want to find an element of that search space that satisfies a known property in the shortest possible time. Classically N operations are needed to solve this type of algorithms, but in the quantum version they are solved making √𝑁 operations.
The algorithm works in the following way : before observing the search set we have no idea which element fulfills our property. Moreover, all positions have the same probability. In this way, we can express it in terms of a state called uniform superposition (Hadamard transformation)
Since all positions have the same probability, when measuring the probability we would obtain 1/𝑁 = 1/2^𝑛. This is where we use a procedure called amplitude amplification. This increases the probability of obtaining the correct item in the final state. Next we will ennumerate the steps to carry out the algorithm
- We begin the amplitude amplification in |𝑠⟩. This state is build as follows
The initial state is
2. We apply a reflection 𝑈𝑓 to the state
Geometrically corresponds to a reflection of the |𝜓t⟩ state over -|𝑤⟩.
3. We apply a new reflection 𝑈s to the state |𝑠⟩. This reflection is as follows 𝑈𝑠=2|𝑠⟩⟨𝑠|−1. In this way, the resultant state is
We perform a rotation of the initial state to the winning state.
4. Return to step 1.
We repeat this algorithm several times until reaching the winning state. In the end, as we said at the beginning we will end up doing √𝑁 operations.
All in all, we have introduced two important algorithms in Quantum Computing. Understanding these algorithms will make the reading of future articles easier.
With this article we finished the theoretical basis of Quantum Computing. In the next articles we are going to explain the theoretical basis of Artificial Intelligence.
Keep it up!
 Michael A. Nielsen & Isaac L. Chuang. Quantum Computation and Quantum Information, 10th Anniversary Edition. Cambridge University Press, 2009.
 Michael A. Nielsen & Isaac L. Chuang. Quantum Computation and Quantum Information, 10th Anniversary Edition. Figure 1.19. Quantum circuit implementing Deutsch’s algorithm. Cambridge University Press, 2009.


Researchers found that making adjustments to existing telecommunications equipment used in optics research could be optimized for quantum photonics research, which could lead to new ways to use these resources for both traditional and quantum communication.
A team from the Department of Energy’s Oak Ridge National Laboratory conducted the series of experiments to gain a better understanding of quantum mechanics and pursue advances in quantum networking and quantum computing, which could lead to practical applications in cybersecurity and other areas.
ORNL quantum researchers Joseph Lukens, Pavel Lougovski, Brian Williams, and Nicholas Peters—along with collaborators from Purdue University and the Technological University of Pereira in Colombia—summarized results from several of their recent academic papers in a special issue of the Optical Society’s Optics & Photonics News, which showcased some of the most significant results from optics-related research in 2019. Their entry was one of 30 selected for publication from a pool of 91.
Conventional computer “bits” have a value of either 0 or 1, but quantum bits, called “qubits,” can exist in a superposition of quantum states labeled 0 and 1. This ability makes quantum systems promising for transmitting, processing, storing, and encrypting vast amounts of information at unprecedented speeds.
To study photons—single particles of light that can act as qubits—the researchers employed light sources called quantum optical frequency combs that contain many precisely defined wavelengths. Because they travel at the speed of light and do not interact with their environment, photons are a natural platform for carrying quantum information over long distances.
Interactions between photons are notoriously difficult to induce and control, but these capabilities are necessary for effective quantum computers and quantum gates, which are quantum circuits that operate on qubits. Nonexistent or unpredictable photonic interactions make two-photon quantum gates much more difficult to develop than standard one-photon gates, but the researchers reached several major milestones in recent studies that addressed these challenges.
“Using this equipment to manipulate quantum states is the technological underpinning of all these experiments, but we did not expect to be able to move in the other direction and improve classical communication by working on quantum communication,” Lukens said. “These interesting and unanticipated findings have appeared as we delve deeper into this research area.”
One such tool, a frequency beam splitter, divides a single beam of light into two frequencies, or colors, of light.
“Imagine you have a beam of light going down an optical fiber that has a particular frequency, say, red,” Lukens said. “Then, after going through the frequency beam splitter, the photon will leave as two frequencies, so it will be both red and blue.”
The members of this team were the first researchers to successfully design a quantum frequency beam splitter with standard lightwave communications technology. This device takes in red and blue photons simultaneously, then produces energy in either the red or the blue frequency. By using this method to deliberately change the frequencies of photons, the team tricked the stubborn particles into beneficial interactions based on quantum interference, the phenomenon of photons interfering with their own trajectories.
“It turned out that off-the-shelf devices can deliver impressive control at the single-photon level, which people didn’t know was possible,” Lougovski said.
Additionally, the researchers completed the first demonstration of a frequency tritter, which splits a beam of light into three different frequencies instead of two. Their results indicated that multiple quantum information processing operations can run at the same time without introducing errors or damaging the data.
Another key accomplishment was the team’s design and demonstration of a coincidence-basis controlled-NOT gate, which enables one photon to control a frequency shift in another photon. This device completed a universal quantum gate set, meaning any quantum algorithm can be expressed as a sequence within those gates.
“Quantum computing applications require much more impressive control levels than any sort of classical computing,” Lougovski said.
The team also encoded quantum information in multiple independent values known as degrees of freedom within a single photon, which allowed them to observe quantum entanglement-like effects without needing two separate particles. Entanglement usually involves two linked particles in which changes made to the state of one particle also apply to the other.
Finally, the researchers have completed quantum simulations of real-world physics problems. In collaboration with scientists at the Air Force Research Laboratory, they are now developing tiny, specialized silicon chips similar to those common in microelectronics in pursuit of even better photonic performance.
“In theory, we can get all these operations onto a single photonic chip, and we see a lot of potential for doing similar quantum experiments on this new platform,” Lukens said. “That’s the next step to really move this technology forward.”
Future quantum computers will allow scientists to simulate incredibly complex scientific problems that would be impossible to study on current systems, even supercomputers. In the meantime, the team’s findings could help researchers embed photonic systems into current high-performance computing resources.
“We have a very diverse and talented team,” Lougovski said. “The most important thing is we’re getting results.”
This research was funded by ORNL’s Laboratory Directed Research and Development program.
UT-Battelle LLC manages Oak Ridge National Laboratory for DOE’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States. DOE’s Office of Science is working to address some of the most pressing challenges of our time. For more information, visit https://energy.gov/science.
— Provided by Oak Ridge National Laboratory


Two newly published studies show that the accuracy and lifetime of silicon qubits are now suitable for large-scale quantum computers.
A dramatic increase in the amount of time data can be stored on a single atom means silicon could once again play a vital role in the development of super-fast computers.
The silicon chip revolutionized most aspects of everyday life since it was invented in the 1950s. It’s changed the way that we communicate with each other, and how we operate almost all everyday items, from cars to airplanes, fridges to televisions and our smart-phones and tablets.
The reason for this is that silicon can be “crafted” into a dazzling array of complex electronic structures and devices, such as the billion or so transistors crammed into each silicon chip.
While modern computers use these silicon chips (or integrated circuits) to perform an array of complex calculations, there are still some important problems that existing computers can’t solve.
For example, medical researchers would love to be able to invent new pharmaceuticals with computer-aided design, much like the way automotive engineers design new cars, but they cannot do this today.
The reason is that the molecules that make up the medicine are not “macro” objects, like a car, but they live in the “micro” or quantum world, which is far more complex to calculate.
In fact, no computer as we know it today will ever be able to properly design such molecular systems. So we must turn to a new type of computer – a quantum computer – in which the “bits” of data used for the calculations are themselves stored on quantum particles, like individual atoms, or electrons.
Such quantum computers are also expected to be able to solve other important problems, such as searching large data sets, or solving complex financial problems.
The search for the best qubit
For the past two decades or so, researchers around the world have been exploring a range of different physical systems to act as the “quantum bits” in such a quantum computer. Now it appears that silicon, which underpinned the previous information revolution, could well provide the key to the next quantum revolution.
Over the past three years, our two research teams at UNSW have shown that silicon can be used to make functioning quantum bits, or qubits. In particular we found that a single atom of phosphorus could be used to tightly hold an electron, which also carries a “spin” (like a tiny magnet) that could be used as a quantum bit. But the binary code (0 or 1) stored on the electron spin got scrambled very quickly, making a fairly poor qubit.
The core of the phosphorus atom also contains a nuclear spin, which could act as an excellent memory storage qubit thanks to its very weak sensitivity to the noise present in the surrounding environment.
Even so, when placed inside a “natural” silicon chip, a phosphorus nuclear spin loses the quantum information encoded on it in less than a second.
Storage time increased
New research published in Nature Nanotechnology – two papers from our groups and one from a Dutch-US collaboration – show that the accuracy and lifetime of silicon qubits are now in a realm that makes them suitable for the manufacture of large-scale quantum computers.
Our teams in Australia have used a specially purified type of silicon that contains only one isotope, called Si-28.
This isotope is completely non-magnetic, because its nucleus has no spin. The electrical properties of a chip of purified Si-28 are identical to those of natural silicon, and so it works equally well for any electronic device.
But when an electron or nuclear spin qubit are configured inside pure Si-28, the absence of magnetic noise allows us to store and manipulate the quantum state with unprecedented accuracy.
In one of the new papers our team demonstrated that we can perform quantum logic operations on a single electron trapped in an “artificial atom”, which is created by small metallic electrodes on the surface of the chip.
These devices are remarkably similar to existing silicon transistors, providing great promise for commercial manufacture. Thanks to the ultra-pure Si-28, we can now reach an accuracy of quantum operations well above 99%. This accuracy is significant because it surpasses the minimum requirement to ensure that the (rare) errors can be corrected using special codes.
In a separate paper we report a similar accuracy, beyond 99%, for the operations on the electron spin held by a phosphorus “natural atom” in the same Si-28 material.
In addition, with the nuclear spin of the phosphorus we have established the new world record for how long quantum information can be held onto a quantum bit in solid state: above 35 seconds, which is an eternity in the quantum world. The accuracy of the operations was a staggering 99.99%.
With the exquisite quantum bits now demonstrated within a silicon electronic device, building functional quantum computers has become a much more realistic prospect. The new quantum revolution might well be built upon the old, trusted and omnipresent silicon microchip.
- M. Veldhorst, et al., “An addressable quantum dot qubit with fault-tolerant control-fidelity,” Nature Nanotechnology (2014); doi:10.1038/nnano.2014.216
- Juha T. Muhonen, et al, “Storing quantum information for 30 seconds in a nanoelectronic device,” Nature Nanotechnology (2014); doi:10.1038/nnano.2014.211
Image: Dr Stephanie Simmons, UNSW


People being people, most of us have gotten used to the idea that the methods we routinely use to protect our information are reliable and safe. This is why you educate your users to check if that little padlock appears in their browser search window before they check their bank balance. It's why we go to the trouble of implementing email encryption as well as secure file transfer systems.
But in the tech industry, change is always on the horizon, which means you need to get used to the idea that what you thought was invulnerable today might easily be threatened tomorrow. One of those changes is quantum computing, and it's a field that's developing quickly. For example, earlier this year, Google announced that it had built the largest quantum computing chip ever: a 72-qubit (a quantum bit) processor.
To put that into context, it's important to explain how a qubit differs from the bit you learned about back in computer science class. Those bits are basic units of information represented by either a 1 or a 0. Qubits, which are represented by the symbol '0> and '1>, can also encompass values of 1 or 0, but can then extend those values to essentially an infinite number of states in between 1 and 0. What happens is that the probability of some number changes as you move between 1 and 0.
We're not going to go into detail about how this works (you can read more about it here), except to say that, by having more potential values between 1 and 0, you can perform some types of computation faster. In some cases, many thousands of times faster than what's possible with today's more advanced desktop CPU architectures, like the Intel i9.
Because of the way quantum computers work, they can be used for jobs that are difficult for these more traditional CPU chipsets. This would include tasks such as multidimensional modeling, simulations, and, yes, codebreaking. It's the codebreaking and encryption cracking that's worrying security experts, and is also freaking out some folks involved with cryptocurrencies as well as those involved with the many other developments being made possible by blockchain technology. Blockchains and cryptocurrencies are, after all, simply very large numbers used to create a unit of whatever currency you're considering. Bitcoin, for example, depends on public key cryptography. Public key cryptography is considered one of the most vulnerable to cracking by a quantum computer, which is part of what's making folks with large Bitcoin investments sweat.
What this means to you is that some types of encryption that you depend on are no longer considered secure. Exactly how that may apply to you is described in more detail in this "Report on Post-Quantum Cryptography" published by the US Department of Commerce's National Institute of Standards and Technology (NIST). What you'll find in this NIST paper is that public key encryption is vulnerable to cracking by using algorithms on a quantum computer. But other means of encryption, including Advanced Encryption Standard (AES), which uses symmetric keys, and Secure Hash Algorithm (SHA-2 and SHA-3), will remain secure with some modifications.
Table 1 - Impact of Quantum Computing on Common Cryptographic Algorithms - Credit: NIST
The most widely used version of AES, which uses 256-bit keys, is actually relatively secure against quantum computing attacks. AES-256 is commonly used for mundane tasks such as Wi-Fi encryption. However, another commonly used version of encryption, secure sockets layer (SSL), uses public key encryption.
Calming Your Quantum Computing Fears
For now, you don't need to worry, though as an IT professional, you should start to plan. Despite the rapid development of quantum computing, researchers don't appear to have reached the point where they can routinely decrypt routine business communications. While that may come someday, you're still fairly safe for now as long as you remember these key points:
SSL communications are still safe; and because they are ephemeral, your users don't need to worry that there'll be a stored copy of their banking session or credit card purchase to be retrieved and cracked at a later date. However, that may change in the future.
AES-256 will be safe, even against quantum attacks, for some time. Unless your data is valuable enough for a nation-state to spend millions of dollars to crack it, you don't need to worry. However, if your business handles national security data, then maybe you need to find a better way and it'd be a good idea to start staying on top of devleoping cryptographic trends.
Age is important. Unless you need to protect your data for decades against future quantum attacks by using advanced algorithms, then some form of symmetric encryption (including AES) will do.
Be prepared for encryption using longer key lengths because those are much harder to crack. Some keys can be found by using brute force techniques but, if the time to crack them by using the fastest quantum computer exceeds the expected age of the universe, then you're probably safe. Longer key lengths will require more computer power to handle, but probably not enough to bog down your systems when they're needed.
Remember that the quality of encryption is only one part of the security puzzle. Poorly executed encryption, weak or faulty software surrounding the encryption, and poor security practices can still expose your critical data through other vulnerabilities. For example, it doesn't help to encrypt your communications if the bad guys can walk into your office and steal the data out of an unlocked file cabinet or, more often, the trash can.
While some forms of encryption now have a limited lifetime, the fact is, you still have time to determine what data you have that may have vulnerabilities because of encryption, and then evaluate whether or not the risk down the road will affect you immediately. For most day-to-day operations, it won't. But if you deal with sensitive data that has a long lifetime, then you need to start planning for the future now.


Bell's theorem is an important philosophical and mathematical statement in the theory of quantum mechanics. It showed that a category of physical theories called local hidden variables theory could not account for the degree of correlations between the spins of entangled electrons predicted by quantum theory. The commonly accepted conclusion of the theorem is that quantum theory is inherently nonlocal in some way, although this is a topic of intense philosophical debate.
Mathematically, Bell's theorem is justified by an important lemma, the CHSH inequality. This inequality bounds the amount of correlation possible between electron spins in a hidden variables theory. The violation of the CHSH inequality in both the theory and experimental results of quantum mechanics proves the theorem.
The historical importance of Bell's theorem is that it proved Einstein, Podolsky, and Rosen [EPR] incorrect in their discussion of the EPR paradox. EPR advocated a philosophy of science called local realism. This philosophy specified that interactions should not be able to communicate instantly across large distances (nonlocally) in violation of relativity, and that systems ought to have a "realistic" definite value of quantities before these quantities are measured.
However, experiments measuring the correlations between spins of entangled electrons seemed to communicate spin states instantaneously between locations (nonlocally). EPR thus concluded that quantum mechanics is incomplete; there must have been some extra hidden variable that set the responses of the entangled electrons to spin measurements at the beginning of the experiment, when both electrons were generated at the same site.
Bell's theorem showed that this interpretation is not true: in order to reconcile theory with experimental results of quantum mechanics, one of locality and realism must be rejected. In fact, in the popular Copenhagen interpretation of quantum mechanics, not only does quantum mechanics "communicate" spin states instantaneously, but before quantities are measured, systems do not take definite values of these quantities: both locality and realism are rejected.
Bell's theorem: No theory of local realism such as a local hidden variables theory can account for the correlations between entangled electrons predicted by quantum mechanics.
The experimental results of quantum mechanics have several loopholes that the past fifty years of research in quantum theory has worked to close. Below two of the major loopholes are discussed:
The detection loophole
It is possible that the detectors at spin measurement sites have less than 100% efficiency, and only detect highly correlated spins, allowing uncorrelated spins to remain undetected. Thus, experiments would report a higher correlation than actually exists, meaning the actual amount of correlation might be explainable by a local hidden variables theory. In the best case scenario, any detectors below 67% efficiency would not close this loophole; in the standard case, about 83% efficiency is required.
Traditional Bell test experiments have ignored this loophole by postulating the fair sampling assumption, which states that the spins measured at each detector are a fair representation of the actual distribution of entangled quantum states produced. While this seems intuitively physically reasonable, it is impossible to prove.
The communication loophole
Since it takes a small but nonzero amount of time to actually perform spin measurements and report the result, it is possible that after one spin is measured, the detector somehow communicates the result at lightspeed to the other detector, which is able to influence the spin of the other particle at measurement time. The only way to close the communication loophole is to separate the two detectors by a large distance and perform spin measurements in such a small amount of time that light could not have traveled between the detectors. This causally separates each detector from the other's influence.
In late 2015,  an experiment whose results were published in Nature claimed to have performed a fully loophole-free Bell experiment demonstrating violation of the CHSH inequality. Similar recent papers claim to have performed loophole-free Bell experiments for entangled photon polarizations, analogous to electron spins.
It has been suggested that the late 2015 result has not quite closed all loopholes due to the possibility of communication between detectors in the past before the entangled electrons were emitted, which might have been able to correlate detectors in some way. This is known as the setting independence loophole. There exists a currently proposed experiment  designed to circumvent this loophole by configuring detector settings using light from two very distant galaxies so far separated that light has not traveled between the two since the big bang. As a result, the detector settings will originate from sources not in causal contact, which means that it will be impossible for the detectors to have become correlated at any point in time.
The proof of Bell's theorem considers an arbitrary local hidden variables theory and shows that any such classical theory attempting to mimic the results of quantum mechanics gives measurement results constrained by an inequality called the CHSH inequality for Clauser, Horne, Shimony, and Holt, although this inequality is also often referred to slightly incorrectly as Bell's inequality.
The CHSH inequality is as follows:
where and are two possible orientations for one Stern-Gerlach detector in a Bell experiment and and are two possible orientations for the second detector. The value gives the correlation of spins along these orientations, and is defined by the expectation of the product of spin states along each direction in quantum mechanics.
The formal derivation of these inequality is fairly extensive, since it introduces a possible hidden variable and then defines the expectations in terms of integrals involving this variable. However, the intuition behind it is simple: each of the expectations along orientation , , , and is at most 1, because each correlation is at best 1 in a classical theory. So one has three plus signs and minus sign in a sum of terms that are bounded by one in absolute value; thus, the sum is bounded by . The tricky part of the derivation lies in manipulating the integral expressions that define the correlations to obtain nice inequalities that don't depend on the hidden variable or detector angle.
An easy example of the violation of the CHSH inequality occurs in experiments measuring the spin in the entangled singlet state of two spin- particles:
The desired correlations in quantum mechanics can be found by taking the expectations of spin measurements made at two Stern-Gerlach apparatuses. Letting be a measurement performed at apparatus A in orientation and similar, consider the following four possible measurements:
where the and orientations are rotated by degrees with respect to and , so that with expectation values taken in the singlet state: The computations of the values given above are tedious but routine exercises in the formalism of spin measurement; see the quantum entanglement wiki for details of how they are performed.
Substituting into the left-hand side of the CHSH inequality, one finds:
This violates the bound of 2 predicted in a local hidden variables theory, as a result of quantum entanglement!
Below, the correlation as a function of angle between orientations and is plotted. The disparity between the classical and quantum predictions is evident, especially at the degree difference used in the above calculation, where each correlation took value where it would have correlation at most in local hidden variables theory.
- Hensen, B. Loophole-free Bell inequality violation using electron spins separated by 1.3 kilometres. Nature, 526, 682–686 (29 October 2015).
- Gallicchio, J. Testing Bell’s Inequality with Cosmic Photons: Closing the Setting-Independence Loophole. Physical Review Letters, 112, 110405 – Published 18 March 2014.
- Gill, R. Bell. Retrieved 22 December 2013, from https://en.wikipedia.org/w/index.php?curid=41434416


The polarization of the photon refers to the “direction” of the axis of the energy field, with the magnetic axis being offset by 90°. Polarization can be a direction like up or down, left or right. Polarization can also mean spin in a clockwise or counter-clockwise direction. The axis of the electric field may be rotating or spinning in time and we would call the photon spin left or spin right. If the axis appears to stay vertical, we do not know for sure that the axis is vertical. We only know for sure that it has the highest probability of being measured in a vertical direction and zero probability of being measured in a horizontal direction.
A simple form of Quantum Entanglement refers to the process of splitting a photon into a pair of photons and sending the two photons in different directions. Both photons start with the polarization of the original photon and the measurement of one photon in one location tells you the polarization of the other photon, or at least the probability of detecting the other photon at a specific angle.
In 2002, Dietrich Dehlinger and M. W. Mitchell posted a paper called “Entangled photons, nonlocality and Bell inequalities in the undergraduate laboratory”. A closer look at this paper allows us to test and refine any Quantum Entanglement model.
Alice and Bob – Entangled Photons
The experiment described and performed by Dehlinger and Mitchell centers around the detection of photon pairs at two different locations. The polarization of a photon stream is first fixed in a specific direction from vertical with a linear polarizer, then the phase of one component is fixed with a birefringent quartz plate. The photon stream is then directed at beta barium borate (BBO) crystals that cause a small fraction of the laser photons to spontaneously decay into photon pairs with the same total energy as the original photon (a process called spontaneous parametric downconversion).
Two single-photon counting modules (SPCMs), are used to detect the photons. One detector is traditionally named Bob and the other Alice. Because the photons of a downconverted pair are produced at the same time they cause coincident, i.e., nearly simultaneous, firings of the SPCMs. Simultaneous firings are considered coincidences if they occur within 25 nanoseconds of each other. The experiment is done by recording the number of coincidences that occur for various settings for the measurement angle of Bob and Alices detectors. The number of coincidences at different observer angles is what must be modelled correctly as a “local realistic hidden variable theory” (HVT).
Modelling Entangled Photons – Close but not Quite
Dehlinger and Mitchell propose a model where each photon has a polarization angle λ. When a photon meets a polarizer set to an angle γ , it will always register as Vγ if λ is closer to γ than to γ + π/2, i.e.,
- if |γ − λ| ≤ π/4 then vertical
- if |γ − λ| > 3π/4 then vertical
- horizontal otherwise.
Dehlinger and Mitchell go on to generate their experimental results and generate the graphic below on the left. The open circles representing Alice at 0° and Bob at 0 to 180°. The closed circles represent Alice settings at 45° and Bob at 0 to 180°.
Represented by icons, the model is plotted against the same angles and produces results shown as calculated on the right. Clearly the calculated results differ from the experimental results. The angle 22.5° shows the most difference between the model and experiment. Dehlinger and Mitchell choose this angle to analyse in detail and show that their experimental results match with quantum physics. In their words “Our HVT is very simple, and yet it agrees pretty well with quantum mechanics. We might hope that some slight modification would bring it into perfect agreement.”.
Refining the Model – adding Probability
To make the model a little more accurate, Animated Physics models the photons as not only having a specific “average” direction, but also as having a “wobble” or “instantaneous” direction. Represented as icons, photons present a more “fuzzy” picture of their polarization. The sample 24° photon, with a 30° wobble, will most of the time be picked up as a vertical, but sometimes when the combined angle is over 45°, it will be picked up as a horizontal. To determine polarity, we use these equations.
- Chance of vertical measurement = (cos((γ − λ)*2)+1)/2
- Chance of horizontal measurement = (cos((γ − λ + π/2)*2)+1)/2
Now consider some angles. A horizontal photon has a 100% chance of getting through a horizontal polarizer. A vertical photon has 0% chance of getting through a horizontal polarizer. A photon with a polarization angle of 45° has a 50% chance of getting through a horizontal polarizer and a 50% chance of getting through a vertical polarizer. Finally, a photon with polarization angle of 22.5° has a 85% chance of getting through a horizontal polarizer and a 15% chance of getting through a vertical polarizer.
Visualizing the Entanglement Model
Let’s start the experiment. To calibrate the equipment, we test that Alice and Bob get maximum matches with both set at 0° (a), they get minimum matches with Alice at 0° and Bob at 90° since the vertical photons have no chance of getting though Bob’s filter (b), with the photon stream set to 45°, Bob and Alice match all photons when both set to 45° (c). The green numbers represent the probability of a photon getting through at that angle.
With the equipment calibrated, we fix the polarizer that Alice is using at 0°, and rotate Bob’s polarizer through a variety of angles and collect our data.
These results demonstrates that this model matches the results of experiment. In fact, the model follows the same cos(γ − λ)² rule that is used by quantum mechanics.
To have fun playing around with photon polarization settings as well as filter angles, click on “Shoot the Photon”.


PT Symmetry Goes Quantum
No physicist would tamper with the conservation of energy—the fundamental law that says energy cannot be created or destroyed. Researchers have, however, taken an interest in devices whose energy is conserved somewhat artificially. Known as PT-symmetric systems , these devices are engineered to have a balance of energy flowing in and out. And they feature many unusual properties, which have, for example, been harnessed to make optical components that only allow light to travel in one direction or that stop the flow of light altogether [2, 3]. Some of these properties might now be realized in the quantum domain. David Zueco of the University of Zaragoza in Spain and colleagues have proposed a realistic circuit in which microwaves interact with a quantum bit (qubit) and that would satisfy the requirements of PT symmetry .
PT symmetry stands for parity-time symmetry. This terminology implies that a physical system looks exactly the same if one performs two operations on it. The first is a parity operation, which swaps left and right so as to exchange the components feeding energy in (the gain) with components allowing energy to escape (the loss). The second is time reversal, which is akin to running a “movie” of the device backwards. A simple example of a PT-symmetric system is a stick that’s being cooled on one end and heated on the other, both at exactly the same rate (Fig. 1, left). If you swap the sources performing the heating and cooling and then time reverse these processes, the system looks exactly the same.
Researchers were initially interested in whether PT symmetry could be a fundamental property of nature, a discovery that would have far-reaching consequences for quantum theory. The reason has to do with quantum theory’s underlying mathematics. Physicists have a strict requirement that the Hamiltonian—the function that is used to calculate a system’s energies—must predict real, not complex, energies. Hamiltonians having the mathematical property of being Hermitian are guaranteed to produce real energies, so quantum theory has been built on the assumption that all viable Hamiltonians are Hermitian. But it turns out that PT-symmetric Hamiltonians also predict real energies and may thus serve as a starting point for an alternative or potentially more fundamental formulation of quantum mechanics.
Textbook quantum mechanics has so far proven resilient to such attempts at a reformulation. But motivated by their potentially interesting properties, experimentalists have realized a variety of PT-symmetric devices by artificially engineering gain and loss in these systems. Most of these demonstrations have involved optical setups, since many methods exist to amplify and dampen light . One experiment, for example, used two coupled ring-shaped resonators—one providing gain, the other providing loss . Using such devices, researchers have explored many of the fascinating aspects of PT symmetry, such as the fact that it gives rise to “exceptional points”—conditions where a system’s allowed modes coalesce into a single mode. An optical PT-symmetric device operated near an exceptional point can behave in unconventional ways, examples of which include a laser that turns on as it incurs more loss or a “topological” waveguide that always transmits waves into a well-defined output mode irrespective of how the waves were injected .
Most of the devices explored so far have been comprised of macroscopic components, and any quantum effects in them were negligible. The paper from Zueco and colleagues indicates that the field is coming back to its roots, with researchers asking how a quantum device possessing PT symmetry would behave. Crucially, the appropriate device would have dynamics that could only be accurately described by the Schrödinger equation, and its gain and loss components would need to be precisely controllable in the lab. Bose-Einstein condensates , optomechanical systems , and several other setups have already been suggested for this task. Zueco and co-workers’ proposed addition to this list of possibilities may prove to be particularly attractive for studying PT symmetry and its ramifications in the quantum realm. That’s because they focus on using the tools of circuit quantum electrodynamics (QED), which is one of the fastest growing areas for studying quantum effects and making technological use of them . In a circuit-QED device, single microwave photons are confined to resonant cavities. Light confined in this way can be made to interact strongly with qubit-like components that have quantized energy levels much like those of an atom.
Zueco and co-workers propose a relatively simple setup comprised of two coupled microwave cavities, each with a qubit placed nearby (Fig. 1, right) . They then imagine achieving a balance of gain and loss in the resonators by driving the qubits with microwaves of the right amplitude and frequency. Using a simple model for this device, the researchers find the value of the coupling between the two resonators that will lead to a PT-symmetric phase transition and its associated exceptional point. They also predict how the transmission of a microwave signal through the circuit would be modified by the onset of this transition.
At first sight, the expected effects are not very different from those predicted by classical models of PT symmetry. But new features are expected to emerge in the quantum domain. Quantum fluctuations are intrinsically linked to both gain and loss through the fluctuation-dissipation theorem. As a result, correlations between the fluctuations of the modes that merge at an exceptional point could lead to a big enhancement in the fluctuation amplitude of the merged mode. The proposed device might also enable the study of the quantum versions of so-called chiral population transfer schemes [9, 10]. Here, one varies a device's parameters such that its allowed energies sweep out a loop around an exceptional point. The way in which the loop is cycled—say clockwise versus counterclockwise—determines the final state of the device, which could be used to build robust and broadband switching elements. By interconnecting two very active fields of research— PT symmetry and circuit QED—the new proposal puts these and other research directions within reach. If researchers succeed in making the proposed device in the lab, we would legitimately be at the starting point of the new field of PT-symmetric quantum mechanics.
This research is published in Physical Review A.
- C. M. Bender and S. Boettcher, “Real Spectra in Non-Hermitian Hamiltonians Having PT Symmetry,” Phys. Rev. Lett. 80, 5243 (1998).
- R. El-Ganainy, K. G. Makris, M. Khajavikhan, Z. H. Musslimani, S. Rotter, and D. N. Christodoulides, “Non-Hermitian Physics and PT Symmetry,” Nat. Phys. 14, 11 (2018).
- T. Goldzak, A. A. Mailybaev, and N. Moiseyev, “Light Stops at Exceptional Points,” Phys. Rev. Lett. 120, 013901 (2018).
- F. Quijandría, U. Naether, Ş. K. Özdemir, F. Nori, and D. Zueco, “PT-Symmetric Circuit QED,” Phys. Rev. A 97, 053846 (2018).
- B. Peng et al., “Parity–Time-Symmetric Whispering-Gallery Microcavities,” Nat. Phys. 10, 394 (2014).
- H. Cartarius and G. Wunner, “Model of a PT-Symmetric Bose-Einstein Condensate in a -Function Double-Well Potential,” Phys. Rev. A 86, 013612 (2012).
- K. V. Kepesidis, T. J. Milburn, J. Huber, K. G. Makris, S. Rotter, and P. Rabl, “PT-Symmetry Breaking in the Steady State of Microscopic Gain–Loss Systems,” New J. Phys. 18, 095003 (2016).
- G. Wendin, “Quantum Information Processing with Superconducting Circuits: A Review,” Rep. Prog. Phys. 80, 106001 (2017).
- H. Xu, D. Mason, L. Jiang, and J. G. E. Harris, “Topological Energy Transfer in an Optomechanical System with Exceptional Points,” Nature 537, 80 (2016).
- J. Doppler, A. A. Mailybaev, J. Böhm, U. Kuhl, A. Girschik, F. Libisch, T. J. Milburn, P. Rabl, N. Moiseyev, and S. Rotter, “Dynamically Encircling an Exceptional Point for Asymmetric Mode Switching,” Nature 537, 76 (2016).


A team of researchers realize the first quantum-logic computer operation between two separate quantum modules in different laboratories.
Today’s quantum computers contain up to several dozen memory and processing units, the so-called qubits. A team of researchers from the Max Planck Institute of Quantum Optics in Garching and ICFO, part of the QIA project, have successfully interconnected two such qubits located in different labs to a distributed quantum computer by linking the qubits with a 60-meter-long optical fiber. Over such a distance they realized a quantum-logic gate – the basic building block of a quantum computer. It makes the system the worldwide first prototype of a distributed quantum computer.
The limitations of previous qubit architectures
Quantum computers are considerably different from traditional “binary” computers: Future realizations of them are expected to easily perform specific calculations for which traditional computers would take months or even years – for example in the field of data encryption and decryption. While the performance of binary computers results from large memories and fast computing cycles, the success of the quantum computer rests on the fact that one single memory unit – a quantum bit, also called “qubit” – can contain superpositions of different possible values at the same time. Therefore, a quantum computer does not only calculate one result at a time but instead many possible results in parallel. The more qubits there are interconnected in a quantum computer; the more complex calculations it can perform.
The basic computing operations of a quantum computer are quantum-logic gates between two qubits. Such an operation changes – depending on the initial state of the qubits – their quantum mechanical states. For a quantum computer to be superior to a normal computer for various calculations, it would have to reliably interconnect many dozens, or even thousands of qubits for equally thousands of quantum operations.
Despite great successes, all current laboratories are still struggling to build such a large and reliable quantum computer, since every additionally required qubit makes it much harder to build a quantum computer in just one single set-up. The qubits are implemented, for instance, with single atoms, superconductive elements, or light particles, all of which need to be isolated perfectly from each other and the environment. The more qubits are arranged next to one another, the harder it is to both isolate and control them from outside at the same time.
Data line and processing unit combined
One way to overcome the technical difficulties in the construction of quantum computers is presented in a new study in the journal Science by first author Severin Daiss, Stefan Langenfeld and colleagues from the research group of Gerhard Rempe at the Max Planck Institute of Quantum Optics in Garching and the Institute of Photonic Sciences (Castelldefels, Spain). The team succeeded in connecting two-qubit modules across a 60-meter distance in such a way that they effectively form a basic quantum computer with two qubits. “Across this distance, we perform a quantum computing operation between two independent qubit setups in different laboratories,” Daiss emphasizes. This enables the possibility to merge smaller quantum computers into a joint processing unit.
Simply coupling distant qubits to generate entanglement between them has been achieved in the past, but now, the connection can additionally be used for quantum computations. For this purpose, the researchers employed modules consisting of a single atom as a qubit that is positioned amidst two mirrors. Between these modules, they send one single light quanta, a photon, that is transported in the optical fiber. This photon is then entangled with the quantum states of the qubits in the different modules. Subsequently, the state of one of the qubits is changed according to the measured state of the “ancilla photon”, realizing a quantum mechanical CNOT-operation with a fidelity of 80 percent. A next step would be to connect more than two modules and to host more qubits in the individual modules.
“Our scheme opens up a new development path for distributed quantum computing”Gerhard Rempe / Director of the Max-Planck-Institut für Quantenoptik
Higher performance quantum computers through distributed computing
Researcher Gerhard Rempe believes the result will allow to further advance the technology. It could enable, for instance, to build a distributed quantum computer consisting of many modules with few qubits that are interconnected with the newly introduced method. This approach could circumvent the limitation of existing quantum computers to integrate more qubits into a single setup and could therefore allow more powerful systems.
Severin Daiss, Stephan Langenfeld, Stephan Welte, Emanuele Distante, Philip Thomas, Lukas Hartung, Olivier Morin, Gerhard Rempe. A Quantum-Logic Gate between Distant Quantum-Network Modules. Science, Vol. 371, Issue 6529, pp. 614-617.
This article was originally published at Max Planck Institute of Quantum Optics newsroom and edited for clarity.
More News?All News
February 15th, 2021
Quantum systems learn joint computing
Researchers realize the first quantum-logic computer operation between two separate quantum modules in different laboratories.
February 5th, 2021
How complex oscillations in a quantum system simplify with time
A team of researchers have shown that in a one-dimensional quantum system, the initially complex distribution of vibrations or phonons can change over time into a simple Gaussian bell curve.
February 1st, 2021
Advances in visualizing large quantum states
A study published in Physical Review A by Quantum Flagship projects PASQuanS and AQTION reports on a novel fast computational method that enables to visualize and thus to better understand large many-body quantum systems


Post written by
Paul Smith-Goodson is Moor Insights & Strategy's analyst in-residence for Quantum Computing.
Qubits are the heartbeat of quantum computers. Their hard-to-imagine properties are what gives quantum machines their awesome computational power.
Superconducting devices, spinning atoms, polarized photons, quantum dots, and trapped ions are not futuristic video games. They are different qubit technologies. Moreover, each qubit type has its peculiar advantages and disadvantages.
Out of all the qubit types, superconducting is the most common. However, trapped ion qubits, a relatively new qubit technology, shows a great deal of promise. In addition to having faster gate speeds, superconducting qubits are solid-state fabrications. On the other hand, trapped ions are more stable and have better connectivity to other qubits than their superconducting counterpart.
Functionally, all qubits depend on strange quantum properties. Instead of classical bits – a one or a zero – a quantum computer’s qubits (quantum bits) can be coded as a one, or a zero, or both a one and a zero. Qubits can also exist in all the possible states at the same time. That condition is called superpositioning.
Bits in a classic computer act individually, while quantum properties allow qubits to become “entangled” with each other. Once entangled, a group of qubits can act as a single qubit. That enables a solution to multiple inputs to appear on a single qubit.
Compared to classical computers that can only work on one computation at a time, superpositioning gives quantum computers the potential to execute millions of simultaneous operations.
Quantum teleportation is another quantum feature. It sounds like science fiction, but it’s not. Instead of teleporting matter, quantum teleportation is limited to sharing quantum states between entangled particles regardless of how far apart they are. In the future, teleportation will be useful for controlling and using qubits in remote quantum servers as well as for telecommunications.
A qubit is a qubit is a qubit … almost
Superconducting heavy hitters
It’s worth noting that Intel is not dependent on superconducting qubits. It is also investigating another qubit technology that operates in silicon, called spin qubit. The quantum state of spin qubits depends on the spin of an electron on silicon. One reason for Intel’s interest in spin qubits is because it is another technology that can leverage Intel’s vast experience in silicon manufacturing.
Rigetti Computing, a recent but impressive California start-up, also uses superconducting qubits. It is a full-stack company that beefed up its application development capability by a recent acquisition of QxBranch.
Superconducting qubit quirks
Superconducting qubits are the most mature of all the qubit technologies. That means we know what improvements are required even though we may not yet know how to do it. Superconducting qubits also have the advantage of being built using existing semiconductor techniques.
Superconducting qubits have a few disadvantages:
- They require near absolute zero temperatures to operate
- They are very susceptible to quantum noise
- They retain their quantum states for short periods
- Limited gate connectivity to qubits
IonQ, an upstart ion startup
IonQ, Alpine Quantum Technologies (Austria), and Honeywell all use trapped ion technology. However, IonQ is its driving force. IonQ was founded in 2015 by Christopher Monroe and Jungsang Kim. Monroe is the Bice Zorn Professor and a Distinguished Professor of Physics at the University of Maryland and Fellow of the Joint Quantum Institute. He is currently the Chief Scientist for IonQ. Kim is a professor in the department of electrical and computer engineering at Duke University.
Building a better ion trap
Trapped ion technology isn’t a radically new concept. It’s used to make some of the most accurate atomic clocks in the world.
Like atomic clocks, IonQ uses an isotope of ytterbium to build its qubits. They start with a neutral atom of ytterbium, then use lasers to remove an electron from the atom’s outer shell. This process converts a regular atom of ytterbium into a ytterbium ion (Yb+).
The ytterbium ion is held in place by electromagnetic fields in a linear ion trap. According to IonQ, because this technology is easy to reconfigure, they can load a hundred or more ions in a linear chain. Also, they can do it without the need to fabricate a new chip. So far, they have used single-qubit gates on a linear chain of 79 ions.
There are many advantages to trapped ion qubits. Compared to superconducting qubits, they need less overhead for error correction. Entangling groups of qubits in a shared trap is easy due to the Coulomb force. Another big plus is the fact that dilution refrigerators are not needed.
Long term view
There is much work to be done before a universal fault-tolerant quantum computer is available. The long-term viability of superconducting and trapped ion qubits looks good. Superconducting qubits will steadily improve as a result of the financial resources of our biggest and best tech companies.
If trapped ion computer researchers can solve the scaling problem with lasers, they have a good chance of exceeding the capabilities of their superconducting counterparts.
Almost all researchers agree we are in the early experimental stages of quantum computing. Best estimates are it will take another 15-20 years for quantum computing to reach maturity. There is an excellent chance that future research will discover better qubit technologies or materials.
Disclosure: My firm, Moor Insights & Strategy, like all research and analyst firms, provides or has provided research, analysis, advising, and/or consulting to many high-tech companies in the industry, including IBM, Google, and Intel, which may be cited in this article. I do not hold any equity positions with any companies cited in this column.Follow me on Twitter or LinkedIn. Check out my website.


A novel method for "plucking" individual particles of light out of a laser pulse could lead to major breakthroughs in quantum computing, researchers say.
Using a combination of supercooled atoms and cutting-edge optical technology, physicists from the Weizmann Institute of Science in Israel were able to extract a single photon from a beam of light.
Individual photons are of great interest to physicists because they are governed by the laws of quantum mechanics rather than the rules of classical physics (which normally apply to light). Many scientists also see photons as a promising candidate to carry information in future quantum computing systems. [Wacky Physics: The Coolest Little Particles in Nature]
"Light composed of photons is already the best carrier of information we have," said Barak Dayan, a senior scientist at the Weizmann Institute of Science, whose lab developed the new method. "But once we move into quantum technologies, we are going to have to use single photons as the carriers of information, so being able to control single photons will be crucial."
In a previous study published in the journal Science in 2014, the researchers showed how the method could be used to create an all-optical router for quantum communication systems. They created a switch to send single photons down different pathways and encode them with quantum information, with the position of the switch determined by its interaction with the photons.
A key benefit of quantum communication is that it is ultrasecure, because the process of measuring any quantum system generally disturbs it, the researchers said. This would normally alert the operator to any eavesdroppers, but according to Dayan, the solution they devised could be used to spy on certain systems.
At present, most single-photon sources are imperfect and occasionally produce more than one photon. "One of the worries is that someone smart could make sure that, if there's one photon, their device doesn't do anything, but if there are two photons, it intercepts the spare one," Dayan said.
This is known as the "photon number splitting attack," and it could be used to decode messages without the interception (of the particle) being detected. Alternatively, operators could use the approach to purify their transmissions by removing extra photons, Dayan said.
Researchers have removed single photons from a beam of light before, in a process called photon subtraction that uses low-reflectivity beam splitters to divert the particles.
But the method is probabilistic, meaning it is hit-or-miss whether a photon will be removed with each pulse of light. In addition, the only way to determine whether the process was a success is to use a photon detector, which absorbs the particle and means it can't be used for anything else. [The 9 Biggest Unsolved Mysteries in Physics]
"In our case, there are two advantages," Dayan told Live Science. "One: In principle, it always happens — it's deterministic. Two: You're not losing the photon, just diverting it, and you can use it for other processes."
The solution uses a single rubidium atom held in place by lasers that cool it to near absolute zero. (Absolute zero equates to minus 273.15 degrees Celsius, or 459.76 degrees Fahrenheit.) Coupled to this is a micro optical resonator — effectively, a 30-micron-wide sphere of glass (for perspective, an average strand of human hair is about 100 microns wide) used to confine light long enough for individual photons to interact with the atom. Light is fed into the resonator using a nanoscale fiber-optic cable.
The researchers rely on a physical effect they call "single-photon Raman interaction," or SPRINT. This causes the atom to block the transmission of light until a single photon is reflected, at which point, it becomes transparent to the remaining photons.
Unlike previous methods of photon subtraction, the SPRINT effect, by its very nature, always removes a single photon from an incoming beam, the scientists said. And though the researchers currently send the extracted photons toward a detector to confirm their findings, the particles of light could be diverted elsewhere, they added.
But Dayan is keen to stress that, for now, his team's work is designed to demonstrate the SPRINT effect, rather than to build a practical quantum communication device. "The realization is very complex — there's a reason no one has done this before," he said. "It combines several technologies, and that combination is very challenging. That's why it has taken us years to build this lab and this experimental setup."
The use of supercooled atoms is beyond the scope of commercial systems, but Dayan said researchers are working on a number of technologies designed to mimic the unique properties of atoms, including quantum dots, which are tiny semiconductors that exhibit interesting quantum effects, such as being able to absorb light from one wavelength and convert it to highly saturated light at a different wavelength.
"Once one of these technologies matures, that effect we have demonstrated will be applicable there as well," Dayan said.
The new study was published online Nov. 23 in the journal Nature Photonics.