Using lasers for quantum information
- Quantum computing
- Quantum teleportation
- Quantum cryptography
- Sources for single or entangled photons
It was only short time after the formulation and acceptance of quantum theory when scientists started to discuss possible benefits of this theory for mankind. The quantum computer, probably the most famous application of quantum theory, is expected to reach incredible computing speeds that enable calculations which were not possible before. Any coupled quantum mechanical system can be used for quantum computing. Solid state systems, trapped ions, atoms in optical lattices, and photons with linear optical elements are at the heart of quantum computer research. First quantum operations have been demonstrated with solid state systems and trapped ions but the race is still open.
The basis for quantum computing is “entanglement”, a quantum mechanical property of a system in which the state of one part of the system is fully linked to the state of another part. The famous “Schrödinger cat” example tries to visualize how strange entanglement is compared to experiences in daily life. Even Einstein doubted this property so much that he and his colleagues Podolski and Rosen published an article in 1935 in which they thought to proof that quantum theory cannot be complete and would have to be substituted by another theory including variables that in quantum theory are still “hidden”. Their “EPR paradox” argument was first theoretically falsified by Bell (“Bell’s theorem”) who showed that quantum mechanics is indeed complete. Until today, Bells theorem was experimentally supported many times. No hidden variables are needed to describe the quantum nature completely.
The strange property entanglement is also the basis for quantum teleportation – where one transfers a quantum mechanical state from one system at one place to another system at another place - and quantum cryptography. The goal of the latter is to send information from one place to another in a completely secure way. Obviously, a quantum cryptography apparatus would be a very powerful and important instrument. Quantum cryptography relies mostly on single on entangled photons and is already commercialized.
Quantum computing is expected to allow for calculations, simulations or operations at a speed that classical computing can never reach. For example, it was theoretically shown that a quantum computer would be able to perform database searches or factorization of large numbers much faster than classical computers. The enormous calculation power of a quantum computer is a consequence of two main ingredients. First of all, the fundamental piece of information is a quantum mechanical two state system (|0> and |1>) called QuBit that – unlike a classical bit which is either 0 or 1 – can be in any superposition (a|0> + b|1>) of the two states. Second, the basic calculations are coherent operations that act on such a superposition state. This way, all possible realizations of anything between |0> and |1> can be computed simultaneously and highly parallel computation is realized. Gate operations, the fundamental operations of computing, were shown with trapped ions and with photon based quantum computers. Using solid state systems (NMR), a proof of principle for quantum computed factorization of the number 15 was demonstrated.
Quantum teleportation is referring to a procedure in which the quantum mechanical state of one object is fully transferred to another object at a different place. It makes use of the non-locality of entanglement that confused not only Einstein. Using a clever sequence of measurements and entanglement operations on photons, the polarization state of one photon could be mapped to another photon completely. Just recently, quantum teleportation between distant matter QuBits was shown using two separate ion traps. Closely related to quantum teleportation and quantum computing is the so-called “quantum logic”. Here, depending on the quantum state of one object a specific state of another object is created. This controlled state preparation was used in metrology to realize one of the best atomic clocks in the world based on aluminum ions.
Quantum cryptography uses quantum physics properties like entanglement and back action of the measurement process on a quantum state to achieve secure communication between a sender (Alice) and a receiver (Bob). The standard approach is that Alice and Bob perform measurements on entangled quantum systems, usually entangled photons, in order to create a key for Alice and Bob. Since they can then use this code to encrypt and decrypt the real message, the quantum cryptography method is called quantum key distribution. The real message is encrypted by Alice according to her measurement results and sent through an open channel (so anyone is allowed to “listen”) to Bob who decrypts the message according to his measurements. Any eavesdropping, so any attempt of a third party to detect the quantum key, can be detected because according to quantum physics laws each measurement influences the quantum mechanical state itself. Eavesdropping would be noticed always. Due to its obvious significance, quantum cryptography research is pushed a lot and many results have been achieved so far. Quantum key distribution over hundreds of km in fiber or over a whole city in free space was shown already while satellite-links of entangled photons between earth stations are currently explored. To proof the usability, a quantum encrypted bank transaction was undertaken.
Sources for single or entangled photons are important tools for quantum computing and quantum cryptography. Single photon sources emitting exactly one photon at a triggered time can be realized in many ways incorporating e.g. color centers or ions in solids, single atoms in traps or optical cavities, trapped ions or quantum dot systems. The most common source for entangled photons is based on spontaneous parametric down conversion. A “blue” photon is converted into two red photons within a non-linear optical crystal. Polarization, momentum and energy of the two photons are strongly correlated. A lot of research on this topic is under way. Main efforts are focused on the development of efficient – ideally full deterministic – sources and realizations with mass production potential.
TOPTICA’s added value
TOPTICA is a highly appreciated supplier for quantum information experiments that involve trapped ions or atoms. Our lasers are successfully applied to cool, trap, optically pump or coherently manipulate ions and atoms. They are fabricated or tuned to the required wavelength such that they can be used to excite single photon emitters. To create entangled photon pairs by parametric down conversion one needs a fundamental laser at half the wavelength of the photon pair in order to initiate the conversion process. Frequently, entangled photons in the near infrared around 800 nm are used and hence violet lasers around 400 nm are required. The development and fabrication of lasers in the UV is TOPTICA’s core competence. We were the first company to produce diode laser systems in the UV and offer a variety of systems with different linewidth/coherence characteristics and power levels for scientific research and industry. No other company has a similar product portfolio. Please contact us to find the best laser for your application.
- Brochure: Scientific Lasers
- Brochure: iBeam smart
- Article: Frequenzkonvertierte cw-Lasersysteme für Forschung und Industrie
- Application Notes: Trapping and quantum computing
- Book recommendation: Oliver Morsch: „Quantum Bits and Quantum Secrets“, Wiley


In a step that brings silicon-based quantum computers closer to reality, researchers at Princeton University have built a device in which a single electron can pass its quantum information to a particle of light. The particle of light, or photon, can then act as a messenger to carry the information to other electrons, creating connections that form the circuits of a quantum computer.
The research, published in the journal Science and conducted at Princeton and HRL Laboratories in Malibu, California, represents a more than five-year effort to build a robust capability for an electron to talk to a photon, said Jason Petta, a Princeton professor of physics.
A Princeton University-led team has built a device that advances silicon-based quantum computers, which when built will be able to solve problems beyond the capabilities of everyday computers. The device isolates an electron so that can pass its quantum information to a photon, which can then act as a messenger to carry the information to other electrons to form the circuits of the computer.
Credit: Princeton University
"Just like in human interactions, to have good communication a number of things need to work out -- it helps to speak the same language and so forth," Petta said. "We are able to bring the energy of the electronic state into resonance with the light particle, so that the two can talk to each other."
The discovery will help the researchers use light to link individual electrons, which act as the bits, or smallest units of data, in a quantum computer. Quantum computers are advanced devices that, when realized, will be able to perform advanced calculations using tiny particles such as electrons, which follow quantum rules rather than the physical laws of the everyday world.
Each bit in an everyday computer can have a value of a 0 or a 1. Quantum bits -- known as qubits -- can be in a state of 0, 1, or both a 0 and a 1 simultaneously. This superposition, as it is known, enables quantum computers to tackle complex questions that today's computers cannot solve.
Simple quantum computers have already been made using trapped ions and superconductors, but technical challenges have slowed the development of silicon-based quantum devices. Silicon is a highly attractive material because it is inexpensive and is already widely used in today's smartphones and computers.
The researchers trapped both an electron and a photon in the device, then adjusted the energy of the electron in such a way that the quantum information could transfer to the photon. This coupling enables the photon to carry the information from one qubit to another located up to a centimeter away.
Quantum information is extremely fragile -- it can be lost entirely due to the slightest disturbance from the environment. Photons are more robust against disruption and can potentially carry quantum information not just from qubit to qubit in a quantum computer circuit but also between quantum chips via cables.
For these two very different types of particles to talk to each other, however, researchers had to build a device that provided the right environment. First, Peter Deelman at HRL Laboratories, a corporate research-and-development laboratory owned by the Boeing Company and General Motors, fabricated the semiconductor chip from layers of silicon and silicon-germanium. This structure trapped a single layer of electrons below the surface of the chip. Next, researchers at Princeton laid tiny wires, each just a fraction of the width of a human hair, across the top of the device. These nanometer-sized wires allowed the researchers to deliver voltages that created an energy landscape capable of trapping a single electron, confining it in a region of the silicon called a double quantum dot.
The researchers used those same wires to adjust the energy level of the trapped electron to match that of the photon, which is trapped in a superconducting cavity that is fabricated on top of the silicon wafer.
Prior to this discovery, semiconductor qubits could only be coupled to neighboring qubits. By using light to couple qubits, it may be feasible to pass information between qubits at opposite ends of a chip.
The electron's quantum information consists of nothing more than the location of the electron in one of two energy pockets in the double quantum dot. The electron can occupy one or the other pocket, or both simultaneously. By controlling the voltages applied to the device, the researchers can control which pocket the electron occupies.
"We now have the ability to actually transmit the quantum state to a photon confined in the cavity," said Xiao Mi, a graduate student in Princeton's Department of Physics and first author on the paper. "This has never been done before in a semiconductor device because the quantum state was lost before it could transfer its information."
The success of the device is due to a new circuit design that brings the wires closer to the qubit and reduces interference from other sources of electromagnetic radiation. To reduce this noise, the researchers put in filters that remove extraneous signals from the wires that lead to the device. The metal wires also shield the qubit. As a result, the qubits are 100 to 1000 times less noisy than the ones used in previous experiments.
Eventually the researchers plan to extend the device to work with an intrinsic property of the electron known as its spin. "In the long run we want systems where spin and charge are coupled together to make a spin qubit that can be electrically controlled," Petta said. "We've shown we can coherently couple an electron to light, and that is an important step toward coupling spin to light."
David DiVincenzo, a physicist at the Institute for Quantum Information in RWTH Aachen University in Germany, who was not involved in the research, is the author of an influential 1996 paper outlining five minimal requirements necessary for creating a quantum computer. Of the Princeton-HRL work, in which he was not involved, DiVincenzo said: "It has been a long struggle to find the right combination of conditions that would achieve the strong coupling condition for a single-electron qubit. I am happy to see that a region of parameter space has been found where the system can go for the first time into strong-coupling territory."
Princeton Professor Jason Petta is available to comment at email@example.com.
John Cramer | EurekAlert!
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The formation of stars in distant galaxies is still largely unexplored. For the first time, astron-omers at the University of Geneva have now been able to closely observe a star system six billion light-years away. In doing so, they are confirming earlier simulations made by the University of Zurich. One special effect is made possible by the multiple reflections of images that run through the cosmos like a snake.
Today, astronomers have a pretty accurate idea of how stars were formed in the recent cosmic past. But do these laws also apply to older galaxies? For around a...
Just because someone is smart and well-motivated doesn't mean he or she can learn the visual skills needed to excel at tasks like matching fingerprints, interpreting medical X-rays, keeping track of aircraft on radar displays or forensic face matching.
That is the implication of a new study which shows for the first time that there is a broad range of differences in people's visual ability and that these...
Computer Tomography (CT) is a standard procedure in hospitals, but so far, the technology has not been suitable for imaging extremely small objects. In PNAS, a team from the Technical University of Munich (TUM) describes a Nano-CT device that creates three-dimensional x-ray images at resolutions up to 100 nanometers. The first test application: Together with colleagues from the University of Kassel and Helmholtz-Zentrum Geesthacht the researchers analyzed the locomotory system of a velvet worm.
During a CT analysis, the object under investigation is x-rayed and a detector measures the respective amount of radiation absorbed from various angles....
The quantum world is fragile; error correction codes are needed to protect the information stored in a quantum object from the deteriorating effects of noise. Quantum physicists in Innsbruck have developed a protocol to pass quantum information between differently encoded building blocks of a future quantum computer, such as processors and memories. Scientists may use this protocol in the future to build a data bus for quantum computers. The researchers have published their work in the journal Nature Communications.
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New Haven, Conn. -- Two major steps toward putting quantum computers into real practice -- sending a photon signal on demand from a qubit onto wires and transmitting the signal to a second, distant qubit -- have been brought about by a team of scientists at Yale. The accomplishments are reported in sequential issues of Nature on September 20 and September 27, on which it is highlighted as the cover along with complementary work from a group at the National Institute of Standards and Technologies.
Over the past several years, the research team of Professors Robert Schoelkopf in applied physics and Steven Girvin in physics has explored the use of solid-state devices resembling microchips as the basic building blocks in the design of a quantum computer. Now, for the first time, they report that superconducting qubits, or artificial atoms, have been able to communicate information not only to their nearest neighbor, but also to a distant qubit on the chip.
This research now moves quantum computing from "having information" to "communicating information." In the past information had only been transferred directly from qubit to qubit in a superconducting system. Schoelkopf and Girvin's team has engineered a superconducting communication 'bus' to store and transfer information between distant quantum bits, or qubits, on a chip. This work, according to Schoelkopf, is the first step to making the fundamentals of quantum computing useful.
The first breakthrough reported is the ability to produce on demand -- and control -- single, discrete microwave photons as the carriers of encoded quantum information. While microwave energy is used in cell phones and ovens, their sources do not produce just one photon. This new system creates a certainty of producing individual photons.
"It is not very difficult to generate signals with one photon on average, but, it is quite difficult to generate exactly one photon each time. To encode quantum information on photons, you want there to be exactly one," according to postdoctoral associates Andrew Houck and David Schuster who are lead co-authors on the first paper.
"We are reporting the first such source for producing discrete microwave photons, and the first source to generate and guide photons entirely within an electrical circuit," said Schoelkopf.
In order to successfully perform these experiments, the researchers had to control electrical signals corresponding to one single photon. In comparison, a cell phone emits about 1023 (100,000,000,000,000,000,000,000) photons per second. Further, the extremely low energy of microwave photons mandates the use of highly sensitive detectors and experiment temperatures just above absolute zero.
"In this work we demonstrate only the first half of quantum communication on a chip -- quantum information efficiently transferred from a stationary quantum bit to a photon or 'flying qubit,'" says Schoelkopf. "However, for on-chip quantum communication to become a reality, we need to be able to transfer information from the photon back to a qubit."
This is exactly what the researchers go on to report in the second breakthrough. Postdoctoral associate Johannes Majer and graduate student Jerry Chow, lead co-authors of the second paper, added a second qubit and used the photon to transfer a quantum state from one qubit to another. This was possible because the microwave photon could be guided on wires -- similarly to the way fiber optics can guide visible light -- and carried directly to the target qubit. "A novel feature of this experiment is that the photon used is only virtual," said Majer and Chow, "winking into existence for only the briefest instant before disappearing."
To allow the crucial communication between the many elements of a conventional computer, engineers wire them all together to form a data "bus," which is a key element of any computing scheme. Together the new Yale research constitutes the first demonstration of a "quantum bus" for a solid-state electronic system. This approach can in principle be extended to multiple qubits, and to connecting the parts of a future, more complex quantum computer.
However, Schoelkopf likened the current stage of development of quantum computing to conventional computing in the 1950's, when individual transistors were first being built. Standard computer microprocessors are now made up of a billion transistors, but first it took decades for physicists and engineers to develop integrated circuits with transistors that could be mass produced.
Schoelkopf and Girvin are members of the newly formed Yale Institute for Nanoscience and Quantum Engineering (YINQE), a broad interdisciplinary activity among faculty and students from across the university. Further information and FAQs about qubits and quantum computing are available online at http://www.
Other Yale authors involved in the research are J.M. Gambetta, J.A. Schreier, J. Koch, B.R. Johnson, L. Frunzio, A. Wallraff, A. Blais and Michel Devoret. Funding for the research was from the National Security Agency under the Army Research Office, the National Science Foundation and Yale University.
Citation: Nature 449, 328-331 (20 September 2007) doi:10.1038/nature06126
& Nature 499, 443-447 (27 September 2007) doi:10.1038/nature06184


The question that intrigued the great American physicist John Archibald Wheeler in the last decades of his life was: “Are life and mind irrelevant to the structure of the universe, or are they central to it?” He suggested that the nature of reality was revealed by the bizarre laws of quantum mechanics. According to the quantum theory, before the observation is made, a subatomic particle exists in several states, called a superposition (or, as Wheeler called it, a ‘smoky dragon’). Once the particle is observed, it instantaneously collapses into a single position.
Wheeler was a scientist-philosopher who introduced the concept of wormholes and coined the term “black hole”. He pioneered the theory of nuclear fission with Niels Bohr and introduced the S-matrix (the scattering matrix used in quantum mechanics). Wheeler devised a concept of quantum foam; a theory of “virtual particles” popping in and out of existence in space (similarly, he conceptualized foam as the foundation of the fabric of the universe).
Wheeler inspired many aspiring young scientists, including some of the greats of the 20th century. Among his doctoral students were Richard Feynman, a Nobel Prize laureate, with whom he coauthored the “Wheeler-Feynman absorber theory”; Hugh Everett, who proposed the many worlds interpretation; Kip Thorne, who predicted the existence of red supergiant stars with neutron-star cores; Jacob Bekenstein, who formulated black hole thermodynamics; Charles Misner, who discovered a mathematical spacetime called Misner space; Arthur Wightman, the originator of Wightman axioms; and Benjamin Schumacher, who invented the term “qubit” and is known for the “Schumacher compression”.
Wheeler suggested that reality is created by observers and that: “no phenomenon is a real phenomenon until it is an observed phenomenon.” He coined the term “Participatory Anthropic Principle” (PAP) from the Greek “anthropos”, or human. He went further to suggest that “we are participants in bringing into being not only the near and here, but the far away and long ago.”
This claim was considered rather outlandish until his thought experiment, known as the “delayed-choice experiment,” was tested in a laboratory in 1984. This experiment was a variation on the famous “double-slit experiment” in which the dual nature of light was exposed (depending on how the experiment was measured and observed, the light behaved like a particle (a photon) or like a wave).
The results of this experiment, as well as another conducted in 2007, proved what Wheeler had always suspected – observers’ consciousness is required to bring the universe into existence. This means that a pre-life Earth would have existed in an undetermined state, and a pre-life universe could only exist retroactively.
Now it appears that Wheeler was a major influence on New York Times bestselling author Deepak Chopra who joined forces with physicist Menas Kafatos to explore some of the most important and baffling questions about human existence. What happens when modern science reaches a crucial turning point that challenges everything we know about reality? In the coming era, the universe will be completely redefined as a "human universe" radically unlike the cold, empty void where human life and our planet is a mere mote of dust in the cosmos.
You Are the Universe literally means what it says--each of us is a co-creator of reality extending to the vastest reaches of time and space. This seemingly impossible proposition follows from the current state of science, where outside the public eye, some key mysteries cannot be solved, even though they are the very issues that define reality itself:
What Came Before the Big Bang?
Why Does the Universe Fit Together So Perfectly?
Where Did Time Come From?
What Is the Universe Made Of?
Is the Quantum World Linked to Everyday Life?
Do We Live in a Conscious Universe?
How Did Life First Begin?
“The shift into a new paradigm is happening,” the duo writes. “All of us live in a participatory universe. Once you decide that you want to participate fully with mind, body, and soul, the paradigm shift becomes personal. The reality you inhabit will be yours either to embrace or to change.”
What these two great minds offer is a bold, new understanding of who we are and how we can transform the world for the better while reaching our greatest potential.
The most distant galaxies billions of light years away, have no reality without you, because everything that makes any galaxy real— with the multitude of stars with their heat, emitted light, and masses, the positions of the distant galaxies in space and the velocity that carries each distant galaxy away at enormous speed—requires a human observer with a human nervous system. If no one existed to experience heat, light, mass, and so on, nothing could be real as we know it. If the qualities of Nature are a human construct arising from human experiences, the existence of the physical universe "out there" must be seriously questioned--and along with it, our participation in such a universe.
Physics has had decades to process the insight of Wheeler, the eminent American physicist, general relativist and quantum physicist, who originated the notion of a participatory universe, A cosmos in which all of us are embedded as co-creators, replacing the accepted universe "out there," which is separate from us. Wheeler used the image of children with their noses pressed against a bakery window to describe the view that kept the observer separate from the thing being observed. But in a fully participatory universe, the observer and the thing observed are one.
The brain isn't the seat of consciousness but acts more like a radio receiver, and perhaps emitter, translating conscious activity into physical correlates. (The radio receiver metaphor describes the feedback loop between mind and brain, which are actually not separate but part of the same complementary activity in consciousness.) To understand our true participation in the universe, we must learn much more about awareness and how it turns mind into matter and vice versa.
These are difficult truths for mainstream scientists to accept, and some would react to them with skepticism, disbelief, or anger. But following the other track of explanation, beginning with physical objects "out there," fails utterly to explain how we are conscious to begin with.
That's why in scattered pockets, some physicists are beginning to talk about a conscious universe, where consciousness is a given throughout Nature. In fact, the founders of quantum mechanics a century ago agreed more with this view, having understood that quantum mechanics implies observation and agency of mind.
In their upcoming book You Are the Universe, they call it the human universe, emphasizing where the whole construct comes from.
Image at top of page: Galaxy cluster MACS J0717, one of the most complex and distorted galaxy clusters known, is the site of a collision between four clusters. It is located about 5.4 billion light years away from Earth. X-ray: NASA/CXC/SAO/van Weeren et al.; Optical: NASA/STScI; Radio: NSF/NRAO/VLA


In the new quantum information technologies, fragile quantum states have to be transferred between distant quantum bits. Researchers at ETH have now realized such a quantum transmission between two solid-state qubits at the push of a button.
Data transmission is the backbone of the modern information society, on both the large and small scale. On the internet, data are exchanged between computers all over the world, most often using fibre optic cables. Inside a computer, on the other hand, information has to be shuttled back and forth between different processors. A reliable exchange of data is also of great importance for the new quantum information technologies that are currently being developed – but at the same time it is also fiendishly difficult. At the ETH in Zurich, a team of physicists led by Andreas Wallraff of the Laboratory for Solid State Physics has now succeeded in transmitting quantum information, at the push of button and with high fidelity, between two quantum bits roughly a metre apart. Their results are published in the scientific journal Nature this week.
Flying quantum bits
The main peculiarity of quantum information technologies, such as quantum computers and quantum cryptography, is the use of quantum bits or «qubits» as the elementary unit of information. Differently from classical bits, qubits cannot just have the value 0 or 1, but also take on so-called superposition states. On the one hand, this results in the possibility to build extremely powerful computers that make use of those superposition states to perform calculations much more efficiently and faster than classical computers. On the other hand, those states are also very sensitive and cannot be transmitted simply using conventional techniques. The problem is that the state of a stationary qubit first has to be transformed into a so-called “flying” qubit, for instance a photon, and then back into another stationary qubit. A few years ago researchers were able to transmit the quantum state of an atom in this way. Wallraff and his co-workers have now succeeded in realizing such a transmission also from one superconducting solid-state qubit to another one some distance away.
To do so, the physicists connected two superconducting qubits using a coaxial cable of the kind that is also used to connect to antenna terminals. The quantum state of the first qubit, which is defined by the number of superconducting electron pairs (also known as Cooper pairs) contained in it, was first transferred to a microwave photon of a resonator using very precisely controlled microwave pulses. From that resonator the photon could then fly through the coaxial cable to a second resonator, inside of which microwave pulses, once more, transferred its quantum state onto the the second qubit. Similar experiments were recently carried out at Yale University.
Deterministic rather than probabilistic
“The important point of our method is that the transmission of the quantum state is deterministic, which means that it works at the push of a button”, Philipp Kurpiers, a PhD student in Wallraff’s lab, emphasizes. In some earlier experiments a transfer of quantum states could already be realized, but that transmission was probabilistic: sometimes it worked, but most of the time it didn’t. A successful transmission could, for instance, be signalled by a “heralding photon”. Whenever the transmission hadn’t worked, one simply tried again. In that way, the effective quantum transmission rate was, of course, strongly reduced. For practical applications, therefore, deterministic methods such as the one now demonstrated at ETH are clearly advantageous.
“Our transmission rate for quantum states is among the highest ever realized, and at 80% our transmission fidelity is very good in the first realization of the protocol”, says Andreas Wallraff. Using their technique, the researchers were also able to create a quantum mechanical entanglement between the qubits as many as 50,000 times per second. The transmission procedure itself took less than a millionth of a second, which means that there is quite a bit of room for improvement in the transmission rate. Quantum mechanical entanglement creates an intimate link between two quantum objects even across large distances, a feature that is used for cryptography or quantum teleportation.
Quantum transfer for quantum computers
As a next step, the researchers want to try to use two qubits each as transmitter and receiver, which makes entanglement swapping between the qubit pairs possible. Such a process is useful for larger quantum computers, which are supposed to be built in the next few years. So far, they only consist of a handful of qubits, but when trying to build larger computers, already for a few hundred qubits one will have to worry about how to connect them most effectively in order to exploit the advantages of a quantum computer in the best possible way.
Much like clusters of single computers used today, quantum computer modules could then be connected together using Wallraff’s technique. The transmission distance, which is currently about a metre, could certainly be increased. Wallraff and his colleagues recently demonstrated that an extremely cold, and thus superconducting, cable could transmit photons over distances of several tens of metres with very little loss. Wiring together a quantum computing centre, therefore, seems to be quite feasible.
Publication: Kurpiers P, Magnard P, Walter T, Royer B, Pechal M, Heinsoo J, Salathé Y, Akin A, Storz S, Besse J-C, Gasparinetti S, Blais B, Wallraff A. Deterministic quantum state transfer and remote entanglement using microwave photons. Nature, volume 558, pages 264–267 (2018), doi: 10.1038/s41586-018-0195-y


These days, losing the manual for some piece of electronics you’ve purchased is notable mostly because you had a printed document to lose in the first place. In the dead-tree dominated days of yore, of course, this was less true. Documentation loss is a major problem in the effort to understand old computer systems, and it’s part of what drives ongoing data preservation efforts across the industry. Until recently, the Zuse Z4 could have been a poster child for this sort of problem.
The Z4 was the brainchild of Konrad Zuse, a German who deserves to be better known than he is for his early, groundbreaking work. Zuse had the misfortune to be making some of his biggest breakthroughs immediately prior to and during World War II. It was Zuse who designed the first high-level programming language from 1942 to 1945. This is remarkable because, as Wikipedia notes, Zuse had no training whatsoever in mechanical computing devices. He independently discovered both propositional calculus and lattice theory, calling them “combinatorics of conditionals” and “study of intervals,” respectively.
The Zuse Z4 is the oldest preserved digital computer in the world and arguably* the first digital computer. The Z4 was developed through the end of the war and was moved multiple times while under construction to keep it away from the advancing Soviet army. After the war, it was expanded and became the second digital computer in the world to be sold. The preserved model is on display at the Deutsches Museum in Munich and is pictured above.
Its documentation, however, was a different story. A recent blog post by the Association of Computing Machinery details how the rare documents were found. Archivist Evelyn Boesch, with ETH Zurich University, contacted Herbert Bruder of the ACM and informed him that her father, René Boesch, had kept a tranche of rare historical documents. These turned out to include a user manual for the Z4 Zuse, as well as notes on flutter calculations. Other documents, dated October 27, 1953, detail what the Z4 was working on. At the time, it was being used to perform flutter calculations on the Swiss FFA P-16 fighter aircraft, which was then in development. Details from the recovered documents show that it took the Z4 50 hours to simulate 2.4 seconds of flight time, which is slightly worse than the current version of Microsoft Flight Simulator.
The ACM blog post notes that “around 100 jobs were carried out with the Z4 between 1950 and 1955,” implying an average per-job computation time of about three weeks.
What We Learn From Manuals Like This
The recovered Z4 manual illustrates why this type of document preservation is so important. From their earliest days, computers were upgradeable — machines like ENIAC were outfitted with the equivalent of RAM upgrades and CPU improvements. In the Z4’s case, support for conditional jump instructions was added post-manufacture. The only problem was, nobody could remember exactly how the feature worked. ACM notes: “However, in a survey a few years ago, the few surviving eyewitnesses could not remember how it was executed.”
Page 8 of the manual provides this information. My German is rusty, my technical German is nonexistent, and frankly, the images are a bit tough to read, so I’m not going to try to translate exactly how the function worked. Without information like this, it would be impossible to precisely replicate or understand how the Z4 embodied or improved upon the computational capabilities of the time.
*The answer to “Who invented the first computer?” is essentially arbitrary and depends entirely on how you choose to define the term “computer.” The UK’s Colossus is declared the world’s first “programmable, electronic, digital computer,” by Wikipedia, but it was programmed by switches and plugs, not a stored program. The Z4 is considered to be the first commercial digital computer but it’s not electronic. The first electronic stored-program computer is the Manchester Baby, but Konrad Zuse’s earlier Z3 could store programs on tape — it just wasn’t electronic. Other obscure machines, like the Atanasoff-Berry Computer, were not Turing-complete and couldn’t store programs, but still contributed critical ideas to the development of computing.
Also, if you were taught that ENIAC was the first computer (or digital computer, or electronic digital computer, etc, ad nauseam), that’s more propaganda than fact. ENIAC was more directly based on machines like Colossus than was known at the time, because the wartime efforts of the British remained classified, while ENIAC was widely celebrated in the media.
Finally, reading up on the history of early computing is a good reminder of how many people, institutions, and companies contributed various technologies and principles to the field. One reason you can subdivide the question of “Who built the first computer” to such a fine degree is that there were so many “firsts” for someone to achieve. There was a time in the 1930s and 1940s when mechanical, electromechanical, and digital systems were sharing space and serious development dollars simultaneously. We don’t have anything remotely equivalent today, and even our wildest architectural departures from the x86 “norm” are still based on digital computing. That could change in the future, if Intel’s MESO architecture comes to fruition and proves capable of replacing CMOS in the long term.
But for now, the 1930s and 1940s represent a tremendously dynamic period in computing history that we don’t really have an equivalent for — though some of the quantum computing work is getting really interesting.


Vincent van Gogh’s “Starry Night” seems to have a special appeal for scientists, who have recreated it using bacteria, among other media, in the past. Now scientists at Caltech have made their own tiny version of the painting—a dime’s width across—out of folded DNA molecules. Some day the same technique could be used to build teensy biosensors, or for targeted drug delivery.
It’s called “DNA origami,” and while many different kinds of shapes have been created using it, this is the first proof of concept that it’s possible to scale up and build large numbers of DNA based devices on computer chips. The Caltech team described their work in a new paper in Nature.
“Everybody thinks molecules are eventually going to be the devices of the future,” Caltech’s Paul Rothemund, DNA origami pioneer and co-author, told Gizmodo. “But how do you connect them? How do you wire them up into larger circuits? How do you do anything with them? You need an interface between the molecular and the macroscopic world, and that’s what this is.”
It’s been ten years since Rothemund made the first amusing shapes by folding strands of DNA. His nanoscale smiley faces, stars, snowflakes, and a miniature map of the Western hemisphere were even displayed at the Museum of Modern Art in New York City in 2008—a true marriage of science and art.
DNA takes the form of a double helix, and encodes all the genetic instructions for manufacturing proteins. It has four repeating chemical bases—known as A, T, G, and C—that are complementary, so A always pairs with T, and G always pairs with C.
To create his special shapes, Rothemund folded a single long strand of DNA back and forth into whatever shape or pattern he desired (determined beforehand with computer modeling), then stuck it all together at strategic points with “staples” comprised of shorter DNA strands. Each V-shaped staple had two “arms” with a base sequence that would bind to its complementary sequence on the longer DNA strand. Then he heated the long DNA strand in a saline solution, and let the whole thing self-assemble into the desired pattern.
It only takes about one week to design the pattern on the computer, and another week to synthesize the DNA, and the actual self-assembly only takes a few hours. “But then you’re stuck with a device that’s floating around in a solution,” said Rothemund. “You can’t combine it with anything else, you can’t wire it into a circuit, it’s even hard to measure its performance.”
If this were ever to find any practical application, Rothemund knew he needed to figure out how to integrate his DNA origami with silicon microfabrication, and he collaborated with IBM scientists to do just that. By 2009, they had discovered that you could make sticky patches on a chip that were the same size and shape as the DNA origami. Simply pour the solution containing the DNA over the surface of the chip and the DNA molecules will stick to those matching patches.
That DNA shape now acts as scaffolding, making it possible to attach other tiny components—like fluorescent molecules. Rothemund likens it to the pegboards typically found in garages to hold various tools, except this is a self-assembled pegboard where the tools find their own positions and stick there, held in place by DNA functioning like Velcro.
Rothemund and his colleagues have been refining this technique ever since. Over the last six years, he and a Caltech postdoc, Ashwin Gopinath, have shown that they can position their DNA origami on pretty much any surface used to make computer chips.
And their latest paper offers the first application: using the method to stick fluorescent molecules into tiny light sources, much like light bulbs screw into lamps. The “lamps” in these experiments are photonic crystal cavities tuned to a specific wavelength of light—in this case, a deep shade of red. (Manmade photonic crystals are engineered with a highly precise honeycomb structure that causes light to reflect off the surface in such a way as to block certain frequencies of light and let others through.)
The injected fluorescent molecules will glow at the tuned wavelength, thereby “lighting” the lamps. But location is key: the molecules will glow more brightly at some locations within the cavity than at other locations. By fiddling with positioning, Rothemund and Gopinath found they could create checkerboard patterns of “hot” and “cold” spots.
That gave them the capability to reproduce other, more elaborate patterns. Gopinath chose to recreate “Starry Night” to demonstrate the technique’s power, because he’d always liked van Gogh’s work. Besides, he had just seen that Doctor Who episode (“Vincent and the Doctor”) in which everyone’s favorite Time Lord goes back to 1890 to help a fictional van Gogh battle an alien monster. Whereas prior work in this area used just a handful of these kinds of devices, Gopinath scaled everything up and stitched together 65,536 of them to recreate van Gogh’s masterpiece.
The next step is to refine this technique even further, perhaps by using different fluorescent molecules or another type of light emitter, like quantum dots, since the ones they used for these experiments tend to burn out quickly. Plus, the colors aren’t as pure as one would like for certain applications, like optical or quantum computing at the nanoscale.
Physicists are likely to be more interested in the potential for doing more fundamental experiments. For instance, an upcoming set of experiments will involve placing multiple emitters inside resonators and trying to get them to sync with each other—a phenomenon called “superadiance” that was first predicted by Robert Dicke back in 1952.
Gopinath likens the effect to how a bunch of metronomes on a table may start ticking out of sync, but will gradually start ticking in unison over time if the conditions are just right. In much the same way, multiple light emitters should sync up as well. “Nobody has yet done a clean experiment, because you have to position emitters at specific distances with respect to each other,” said Gopinath. This new paper provides a possible way to do that.


The Google quantum computer “Sycamore” recently solved an equation in 200 seconds, a task that would have taken a supercomputer thousands of years. Photo: Google
The Basics of a Quantum Computer
Mar 5, 2020
by Carlos M. Gonzalez
Companies like IBM, Google, and Honeywell—that has just unveiled its new quantum computer in partnership with Microsoft—are all developing quantum computing systems to tackle complex computations for both business and engineering services.
Understanding how a quantum computer works and operates is an ongoing puzzle, even to its own developers. The larger question is, can quantum computers become the future of computing and what role will engineers play in their development?
How Does a Quantum Computer Work?
First, to understand quantum computing, we need to understand three basic principles of quantum mechanics, and how quantum computers manipulate those mechanics to store information differently.
For regular computers, bits are the basic unit of information. They are binary, that is, they can be either on, represented by a “1,” or off, noted by a “0.” This binary code is the language of computer coding. Arranging the 1’s and 0’s into different configurations enables us to see an image, a video, a text, or a graphic on any computer.
The basic unit of information in quantum computing is the qubit, and it has many possibilities.
"Physicists often think of a qubit like a little globe, with '0' at the north pole and '1' at the south pole," said Marissa Giustina, a Google research scientist and quantum electronics engineer. "The qubit’s configuration is represented by a point on the globe. In manipulating the qubit, we can send any point on the globe to any other point on the globe."
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Quantum computing uses the mechanics of superposition, entanglement, and interference to create states of exponential scalability.
- Superposition is a combination of states that would typically operate independently of each other. Dr. Talia Gershon, senior manager of Q Experiences at IBM Research, describes superposition as a qubit operating in both a “yes” and a “no” state, much like a coin spinning on a table that can be both heads and tales. Superposition reflects actual behavior in which an object can be in multiple states at the same time.
- Entanglement creates a system of qubits. If two qubits are entangled, they will both show the same result when measured. To use the coin analogy, Dr. Gershon explains that two coins spinning at the same time, would both have equal value regardless of which face is up when they stop spinning. If one qubit is measured as open, its entangled qubit is measured open.
- Interference is the act of quantum qubits operating as a wave. These waves can work in unison or opposite of each other. When the waves are in phase, their amplitudes add, creating constructive interference. When they are out of phase, their amplitudes cancel out, causing destructive interference. This is very similar to how noise-canceling headphones work. “By using interference, we can amplify the signals leading to the right answer, and cancel out the signals leading to the wrong answer,” Dr. Gershon said.
Like a conventional bit, it can be either "1" or "0". But it can also be in both those states at the same time. This means that each qubit has four potential states—"1-1", "1-0", "0-1", and "0-0"—though it can only be in one of those states at a time. These grow exponentially with more qubits. So if you have 100 qubits, there are 2 to 100th power of possible states.
Google’s quantum computer, for example, can perform complex test computations within 200 seconds. The most powerful supercomputers would spend years to finish the same computations.
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For each of these states, the value of qubit can only be measured in 1’s and 0’s. So while information can be stored in multiple states, computing those states still require a binary relationship. This is the current hurdle of quantum computing. Researchers are working on how to scale up quantum computers and how to measure the quantum processors accurately.
What is Inside a Quantum Computer?
The inside of a quantum computer resembles a massive fridge. The dilution refrigerator is layered in tiers that create colder and colder levels until it reaches super freezing temperatures of 10 to 15 milliKelvin, which is colder than temperatures in outer space. These temperatures allow quantum processors to create superposition and entanglement scenarios.
IBM’s quantum computer can be broken down into seven areas. It starts with the qubit signal amplifier. This first is one of two amplifying stages where the cooling starts to a temperature of 4 Kelvin. The second area is the input microwave lines, where attenuation is applied to each stage of the refrigerator to protect the qubits from thermal noise while controls and signals are sent to and from the processor.
The third area is the superconducting coaxial lines that direct the signals between the first and second amplifying stages. The fourth area is cryogenic isolators, which enable the qubit signals to go forward while preventing noise. The fifth area is quantum amplifiers inside a magnetic shield, which captures and amplifies readout signals while minimizes noise.
The sixth area is the cryoperm shield. The shield is where the quantum processor sits, and the qubits are found within the quantum processor. It protects the quantum processor from the electromagnetic radiation to preserve its quality. Lastly, the seventh area is the mixing chamber, the lowest part of the refrigerator. It provides the necessary cooling power for the processor to function.
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This device is massive, and the processors are its finite resource. Google’s quantum computer Sycamore is a near intermediate noisy quantum (NISQ) device. The Sycamore has about 50 qubits and a finite lifetime. A NISQ device will perform up to a few thousand quantum operations, and then you will need to replace the quantum processor with new qubits. The limited computational lifetime forces engineers to carefully decide which computations will be performed.
How Engineers Will Impact Quantum Computing?
To date, quantum computer use cases are limited and have revolved around solving complex data scenarios that would be difficult for supercomputers.
“It is very early for quantum computing, and we are building assembly languages so you can interchangeably program for a supercomputer or a quantum computer. We are not envisioning quantum computers replacing classical computers anytime soon,” Dr. Gershon said.
“We think quantum computers are going to be used to accelerate the types of computations that are hard for classical machines. Simulating nature is something that is really hard—such as modeling atomic bonding or electronic orbital overlap. Instead of writing out a large summation over many terms, you can now simulate the system directly onto a quantum computer.”
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"Quantum computing will enable us to tackle complex scientific and business challenges, driving step-change improvements in computational power, operating costs, and speed," said Honeywell's Chief Executive Darius Adamczyk in a recent press release.
Honeywell has partnered with two quantum software and algorithm providers, Cambridge Quantum Computing and Zapata Computing, to launch and to research use cases for their quantum computing.
"Materials companies will explore new molecular structures. Transportation companies will optimize logistics. Financial institutions will need faster and more precise software applications. Pharmaceutical companies will accelerate the discovery of new drugs. Honeywell is striving to influence how quantum computing evolves and to create opportunities for our customers to benefit from this powerful new technology," said Adamczyk.
A prime example of using quantum computing is for chemistry applications. Quantum computers can predict the behavior of molecules in a solar cell, because the same laws of physics govern qubits in a quantum processor. It provides engineers with a more accurate model of how their design will function.
While computer processing is advanced, the systems used to create a quantum computer are still based on traditional engineering.
“To build the dilution refrigerator, traditional mechanical cryogenic engineering is used to achieve the super cold temperatures,” said Yu Chen, a quantum electrical engineer at Google. “Also, the control signal used to command the qubits are based on classical micro-electrical engineering principals.”
Creating new systems for quantum computers will be the task for design engineers. For example, in order to control 50 qubits, a computer will need more than 100 control channels. Determining how to create stable and scalable connections will be the task for electrical engineers.
On the mechanical side, creating stable heating and cooling systems will be the main task. Vacuums are used to create the low temperatures, and the challenge is to figure out how vibration will affect the computer’s systems. Mechanical engineers will need to design a cooling system capable of the low Kelvin temperatures without damaging the equipment.
“There is a lot of unknown in terms of how the current environment will interact with quantum systems. We will need a lot of help from the engineering community to reach the next stage,” Chen said. “How do we modify classical computing facilities to house quantum computers? How should we build logic facilities? What are the mechanical concerns to house a quantum computer? These are questions that the engineering community will need to answer once the quantum computer begins to scale.”
Carlos M. González is special projects manager.


Image credit: archy13 / Shutterstock.com
Right now, in the world of computing the race is on to create a truly useful and effective quantum computer. Next generation super-computers such as these would pave the way for solving a new realm of problems that are incomprehensible to existing computers.
The benefit of quantum computing is that unlike classical computing it can make good use of the unique ability possessed by subatomic particles to exist in more than one state at any given time. What this means is that whereas the current generation of computers use bits – which is a single piece of information that can exist in one of two states, one or zero – quantum computers make use of quantum bits known as ‘qubits’, instead. Therefore, they have the ability exceed traditional information storage capabilities of one or zero due to the fact they can exist in any superposition of these values.
However, the coherence of a qubit, i.e. its preservation of the superposition, is in a fragile quantum state which be easily destroyed by environmental ‘noise’. Furthermore, this noise that can be generated by electronic systems, heat dissipation, or any impurities present in the qubit itself can lead to critical errors that could prove demanding to rectify.
MIT and Dartmouth College researchers have successfully designed and coordinated the first set of laboratory tests that utilizes a breakthrough method that allows for effective monitoring and detection of the characteristics that troublesome environmental noise generates. This significant leap may offer new insights into microscopic noise mechanisms to further assist the engineering of state-of-the-art processes to protect the fragile qubits.
This is the first concrete step toward trying to characterize more complicated types of noise processes than commonly assumed in the quantum domain. As qubit coherence properties are being constantly improved, it is important to detect non-Gaussian noise in order to build the most precise quantum systems possible.
Lorenza Viola, Professor of Physics, Dartmouth
The technique developed by the researchers separates non-Gaussian noise from the background Gaussian noise, then they were able to reconstruct comprehensive sets of information about these signals by using signal-processing techniques. Thus, offering researchers the ability to generate more realistic noise models, which could go some way toward further protecting qubits by enabling vigorous processes that shields them from certain noise types. This is necessitated by the fact that the development of qubits with fewer defects than previous iterations may lead to an increased presence of non-Gaussian noise.
This is akin to being at a loud party where although it may be difficult to maintain a steady conversation it is still possible, however, when individual voices start to stand-out it can contribute to a breakdown in one’s own thought-process making it much more difficult to sustain continual discussion. “It can be very distracting”, stated William Oliver, an associate professor of electrical engineering and computer science, professor of the practice of physics, MIT Lincoln Laboratory Fellow, and associate director of the Research Laboratory for Electronics (RLE).
For qubits with many defects, there is noise that decoheres, but we generally know how to handle that type of aggregate, usually Gaussian noise. However, as qubits improve and there are fewer defects, the individuals start to stand out, and the noise may no longer be simply of a Gaussian nature. We can find ways to handle that, too, but we first need to know the specific type of non-Gaussian noise and its statistics.
Throughout their research, the team determined that qubits with superconducting capabilities can act as sensors for the noise they generate themselves. In the experiments, they introduced non-Gaussian ‘dephasing’ noise as engineered flux noise that interrupts the coherence of the qubit, this can then be utilized as a measuring tool. “Usually, we want to avoid decoherence, but in this case, how the qubit decoheres tells us something about the noise in its environment,” Oliver says. A detailed description of the process was published in a paper in the journal Nature Communications.
However, while the study won’t make large-scale quantum computers manifest in the immediate future it is still considered highly valuable work as the team bridged the gap between theory and practice. “This research started on the whiteboard. We didn’t know if someone was going to be able to put it into practice, but despite significant conceptual and experimental challenges, the MIT team did it,” said Felix Beaudoin, a former Dartmouth postdoctoral student and vital part of Professor Viola’s team.
The progressive impact this study could have on the future of quantum computing is far-reaching, as well as preserving the integrity of qubits it would enable the computers to be more precise, robust, and dependable. Once the gate is open it is expected quantum computing will allow machine learning to accelerate exponentially which means taking giant steps towards advanced AI systems and even reducing the time to solve a problem from hundreds of years to just a few seconds. In short, we could see quantum computing solving some of humanities most complex and difficult questions.


Through the Internet, humans have connected the world. People are closer to each other than ever while still remaining apart. The next phase of the the Internet will be about connecting things. The Internet of Things will be central to the infrastructure that we build. (The “Futurist’s Cheatsheet” series surveys technologies on the horizon: their promise, how likely they are, and when they might become part of our daily lives. This article is Part 5.)
What Is It?
Think of a thing. Really, it could be anything. A chair, a toaster, parts of a car, the lights in your house, the electricity meter, the security cameras in your offices, a fire hydrant, traffic lights … really, anything or everything that can exist could be connected to the Internet. Another name for the Internet of Things is a network of things. The network can monitor your home, your car, infrastructure (utilities such as electricity or water), traffic patterns and a variety of other possibilities to create a more informed and responsive system through data analysis.
How It Works
Do you really need an Internet-connected toaster? Probably not. But, the toaster is a good place to start when discussing the Internet of Things.
What would you expect from a smart toaster? Perhaps a touch screen on which to schedule cooking. It could be connected to the coffee pot, enabling the perfect breakfast for you as soon as you wake. Your toaster could be programmed from your computer or a mobile app. Say you are laying in bed and know you are going to sleep in the next day, pull out your smartphone and reprogram the toaster to start an hour later.
A toaster could have its own IP address on the Internet. In theory, you could visit your toaster’s site. Giving things a full IP address is one way to tie a thing to the Internet. Another way, and the way in which many things will be tied to the Internet, is for a thing to just have the ability to connect to the Internet, without and IP address.
Now, imagine that there is no digital interface on your toaster. In this case it is just a toaster that happens to have cellular or Wi-Fi capabilities and sensors to monitor how well it performs. It sends sensor data back to the manufacturer through Internet nodes and portals without an individual IP address. The manufacturer uses this data to know how its product is working in the wild, how often it is used, and use this data to make a better toaster.
Go back and replace the word toaster with anything, say, a power meter. The same concepts apply. An Internet of Things can use the Web as an interface, or just use the Internet to move data. That data can be used to interact with the network of things or just as a pipeline where data moves two ways, analyzed and used to make objects smarter and more responsive to people’s needs.
There are so many ways that an Internet of Things could impact people’s lives that it is hard to describe everything. Distilling it to a few key areas helps define what the scope of an Internet of Things could be: infrastructure (buildings and utilities), consumer (cars and homes), health care and businesses (consumer products and retail locations).
Weather-related sensors could help agriculture by monitoring the moisture in the air or ground and give farmer’s warning about droughts. Smart buildings can provide enhanced security for the people that enter them or warning on disasters such as earthquakes. Connected cars can improve traffic flows or allow functions to be controlled remotely. Items within the home (such as the toaster) can be controlled and monitored and even connected to each other.
Health care is an interesting avenue for the Internet of Things. Certain aspects of the body could be connected to the Internet. Heart sensors could give patients and doctors data to prevent disease. Sensors that monitor white blood cells could give cancer or AIDS patients warning of a relapse.
The scope and impact of the Internet of Things is almost limitless. It is just up to the innovators of the world to be creative and find ways to make it work.
Much of the base technology that will enable and Internet of Things is available. The challenge now is to refine that technology and make it ubiquitous.
A truly connected society involves a concerted effort from many different industry sectors such as telecommunications (the lines that would do the actual connecting), to device and appliance makers that would implant sensors and connectivity into things. Software developers would then have to create the interfaces. There are also security and privacy issues, such as keeping this mountain of data safe and away from prying eyes. Wireless standards and infrastructure also need to improve to handle all of the data that would be generated.
When Will It Be Ready?
Many of the innovations we have written about in The Futurist’s Cheat Sheet have seeds in today’s technology. That is the same for the Internet of Things. The technology is present, but the infrastructure and stability behind it needs to be improved.
Companies specializing in machine-to-machine functions such as Numerex and KORETelematics are already in the process of designing the connected world and building business models that will help define the Internet of Things.
The progression will be slow. There is no event horizon where suddenly the technology that is only a theory becomes a reality.
The Internet of Things is something that must be built and refined, not something like quantum computing that is waiting for a significant technological breakthrough. In five years we will start seeing more connected cars and homes.
Infrastructure like smart grids and utilities will take longer to build and we will see it evolve over the next 10 years and more. The Internet of Things will become embedded in our lives and the growth will not stop during out lifetimes.
European Commission: Cluster of European Research Projects: Vision and Challenges for Realising the Internet of Things (March 2010)
ReadWriteWeb: Top 5 Web Trends of 2009: Internet of Things
ReadWriteWeb: Top 10 Internet of Things Developments of 2010
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A proof-of-concept published today in Nature promises warmer, cheaper and more robust quantum computing. And it can be manufactured using conventional silicon chip foundries.
Most quantum computers being developed around the world will only work at fractions of a degree above absolute zero. That requires multi-million-dollar refrigeration and as soon as you plug them into conventional electronic circuits they’ll instantly overheat.
But now researchers led by Professor Andrew Dzurak at UNSW Sydney have addressed this problem.
“Our new results open a path from experimental devices to affordable quantum computers for real world business and government applications,” says Professor Dzurak.
The researchers’ proof-of-concept quantum processor unit cell, on a silicon chip, works at 1.5 Kelvin – 15 times warmer than the main competing chip-based technology being developed by Google, IBM, and others, which uses superconducting qubits.
“This is still very cold, but is a temperature that can be achieved using just a few thousand dollars’ worth of refrigeration, rather than the millions of dollars needed to cool chips to 0.1 Kelvin,” explains Dzurak.
“While difficult to appreciate using our everyday concepts of temperature, this increase is extreme in the quantum world.”
Quantum computers are expected to outperform conventional ones for a range of important problems, from precision drug-making to search algorithms. Designing one that can be manufactured and operated in a real-world setting, however, represents a major technical challenge.
The UNSW researchers believe that they have overcome one of the hardest obstacles standing in the way of quantum computers becoming a reality.
In a paper published in the journal Nature today, Dzurak’s team, together with collaborators in Canada, Finland and Japan, report a proof-of-concept quantum processor unit cell that, unlike most designs being explored worldwide, doesn’t need to operate at temperatures below one-tenth of one Kelvin.
Dzurak’s team first announced their experimental results via the academic pre-print archive in February last year. Then, in October 2019, a group in the Netherlands led by a former post-doctoral researcher in Dzurak’s group, Menno Veldhorst, announced a similar result using the same silicon technology developed at UNSW in 2014. The confirmation of this ‘hot qubit’ behaviour by two groups on opposite sides of the world has led to the two papers being published ‘back-to-back’ in the same issue of Nature today.
Qubit pairs are the fundamental units of quantum computing. Like its classical computing analogue – the bit – each qubit characterises two states, a 0 or a 1, to create a binary code. Unlike a bit, however, it can manifest both states simultaneously, in what is known as a “superposition”.
Cheaper and easier to integrate
The unit cell developed by Dzurak’s team comprises two qubits confined in a pair of quantum dots embedded in silicon. The result, scaled up, can be manufactured using existing silicon chip factories, and would operate without the need for multi-million-dollar cooling. It would also be easier to integrate with conventional silicon chips, which will be needed to control the quantum processor.
A quantum computer that is able to perform the complex calculations needed to design new medicines, for example, will require millions of qubit pairs, and is generally accepted to be at least a decade away. This need for millions of qubits presents a big challenge for designers.
“Every qubit pair added to the system increases the total heat generated,” explains Dzurak, “and added heat leads to errors. That’s primarily why current designs need to be kept so close to absolute zero.”
The prospect of maintaining quantum computers with enough qubits to be useful at temperatures much colder than deep space is daunting, expensive and pushes refrigeration technology to the limit.
The UNSW team, however, have created an elegant solution to the problem, by initialising and “reading” the qubit pairs using electrons tunnelling between the two quantum dots.
The proof-of-principle experiments were performed by Dr Henry Yang from the UNSW team, who Dzurak describes as a “brilliant experimentalist”.
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Quantum computing is one of the most interesting fields of study nowadays, both from theoretical and pragmatic point of views. A universal quantum computer can potentially solve certain problems, as factorizing numbers, much faster and with fewer resources than a classical one 1. This developing technology is based on the use of quantum mechanics as a new framework for computation. On quantum computers the information is not store, neither compute, in classical bits, but in quantum bits. The principal difference between classical and quantum bits is that qubits can be in superposition of two different states. Unfortunately, there is a general agreement about the state of the art, and it is that we are still far from having an operable universal quantum computer. Recent experimental groups have developed different architectures, but they are still small and they can operate just a few qubits. Hence, the principal concern regarding the real utility of quantum computers is the possibility of designing one that handles a few hundred qubits, at least.
One milestone in the direction of quantum computing has been recently released, by the private company DWave . This company has developed an operable quantum simulator of 128 qubits, called D-Wave One. Furthermore, they are going to install a new version, called D-Wave Two, with capability for operating with 512 qubits, for a new laboratory created by Google and NASA 2. Hence, the question now is what this new machine does, and if it is really a quantum computer.
What is D Wave and which problem can it solve?
D-Wave is based in a technology called superconducting flux qubits. The qubits it operates are grouped in 4×4 units, with different connections between them. A scheme of the architecture is shown in Fig. 1. The first version has 128 qubits, but tot all of them can be used for computing, as some of them are disconnected from their neighbors.
This new machine should be considered a quantum simulator more than a universal quantum computer. It does not perform universal quantum computation, because it cannot make arbitrary operations in all qubits.
Basically the principal problem D-Wave can solve is the problem of quantum annealing. That is to find the ground state, that is the state with lowest energy, of an Ising spin glass model. This problem is known to be a non polynomial (NP) hard problem. Because of that when the dimension of the problem growths linearly the complexity of finding a solution growths in an exponential way. There are no indications that allow us to conclude that a quantum computer can solve this problem in a non-exponential way, but in any case it can give an important speedup over classical computers.
A fair question regarding this, or any, new technology is which really useful problems can it solve. Directly, it can solve only annealing, but this is interesting enough, because this problem is as hard as the hardest problem in the NP class. In this class there are many popular problems, as the salesman, factoring or minimization in artificial intelligence. If any of these problems is mapped to the problem of annealing it could be solved by the use of this new technology. The way of mapping each concrete algorithm is, of course, highly non trivial.
How can D-Wave be tested?
Recently, a test of the quantumness of D-Wave has been performed 3. For this purpose several researchers performed computer simulations in both the quantum machine and classical computers. They compare principally three approaches, D-Wave, a classical simulation of how quantum annealing should perform in quantum simulators, and the best known classical. For obvious reasons, the last two approaches were run in classical computers.
In Figure 2, the principal differences between these three approaches are displayed. For this simulation the authors selected 1000 different configurations and they launched each of them 1000 times, with different initial states. The plot shows how many configurations were found as a function of the success probability of finding the correct answer for each configuration.
The interpretation of this figure is clear. Classical and quantum annealing exhibit very different behaviors. For classical algorithms the distribution presents only one maximum, and most of the problems have one half probability of being solvable. For the quantum case there are many “easy” and “hard” problems and that leads to a distribution with two maxima, closed to zero and one. These result points in the direction that really D-Wave behaves in a quantum way, as its results are closer to the simulation of a quantum system than to a classical algorithm.
Finally, the authors also analyzed the scaling of the computation time with the size of the problem, but the results are inconclusive. The optimization problem for 108 qubits is quite easy, and it is difficult to see if there is a quantum speedup. This question could be potentially addressed by the next generation of quantum annealers, which are expected to have 512 qubits.
Based in the research performed Boixo et al there are many indicators that D-Wave is a genuine quantum annealer. On the other hand, it is not faster than classical ones. In any case it is definitively a milestone in the field of quantum computer, because it also represents a paradigm shift. Instead of creating a universal quantum computer with a few qubits, the developers of D-Wave have focused in a quantum device with many qubits that can perform only one task.
Only time can clarify if this is the beginning of a new time in quantum computing. If D-Wave Two really beats classical computers in annealing it will be the first time a quantum device can compute a general problem better than classical ones. This problem can be, at least potentially, useful to many other fields.
- Quantum Computation and Information. Nielsen and Chuang. Cambridge University Press. ↩
- Google and NASA snap up quantum computer. N. Jones. Nature News. doi:10.1038/nature.2013.12999 ↩
- S. Boixo, T.F. Ronnow, S.V. Isakov, Z. Wang, D. Wecker, D.A. Lidar, J.M. Martinis and M. Troyer. arXiv 1304.4595 [quant-ph] ↩


I am a Software Engineer with a passion for science, technology, business, and everything in between.
Just like that, virtually every single computer on earth can be considered obsolete. Even if a manufacturer decides to release a new computer model within the next six months, it’s out of date.
How is this possible? The fact is, Google, IBM, and other tech giants are working around the clock to engineer technology based on quantum mechanics, which makes our current computers look like toys. This is a brand-new type of technology that has never been developed before.
So just like a horse and buggy is not the same as a car, our modern-day computers are not at all like the newly developed quantum computers. They have so much more processing power and are capable of cracking problems that current technology cannot even touch.
What Is a Quantum Computer?
For decades, computers have always used bits and the binary system to compute information. This system consists of zeros and ones and gives an ordinary computer a precise command. The machine thus responds by performing the appropriate activity, whether it be completing a job or producing the data requested.
A quantum computer uses qubits, which is a more complex quantum version of the traditional binary system leaving endless possibilities. Unlike our current computers, the jobs or instructions given to the machine can take place under a measure of uncertainty with the help of superposition, entanglement, and interference. But what does this mean?
In the quantum world, superposition can be likened to a constant spin of a coin having zero and one individually on each side. Therefore, there is some probability of the outcome being zero and some probability of it being one. Also, this probability does not have to be 50/50, leaving a measure of uncertainty when transferring data.
Entanglement incorporates two qubits that are in a superposition spinning between zero and one, and they are mimicking each other in movement. This means that when you alter the state of one particle, you subsequently change the stated of the other particle, no matter how far apart these particles are. The particles are joined together but not by a physical connection.
And lastly, interference is the wave movement created by particles called beating, as the data is transmitted. Superposition produces patterns of interference, which at times can work in harmony or cancel each other out when processing data. If you are scratching your head, it just means that you are slowly beginning to get it.
To gain a further understanding of quantum computers, you have to grasp what quantum mechanics is. Quantum mechanics is the scientific theory behind the tiniest parts of the world around us, such as molecules, atoms, and other subatomic particles.
Based on extensive research, scientists have been able to engineer quantum chips in hermetically sealed glass laboratories and place them into the circuit boards of temperature-controlled quantum computers. The metal on a silicon chip, also known as superconducting qubits, is how the particles of information are transferred from point A to B.
Can It Reverse Time?
Within a carefully controlled environment, scientists were able to use a quantum computer to reverse a process that had previously taken place.
How was this done? Within the theory of quantum mechanics, the atoms and various particles are described as a wave function. It is not the same as a tangible wave, but it’s an abstract mathematical portrayal of the position and movement of an electron. Even so, these calculations of its position are all probability, and nothing is ever exact.
Nevertheless, researchers were able to take these calculations and use the law of thermodynamics to reverse a process that had taken place by two qubits. Although difficult and problematic in a standard atmosphere, in a quantum environment it has become a straightforward procedure to complete. This does not mean that a time machine has finally been created. But they still have effectively been able to write a computer program that reverses the system back to its original state 85% of the time.
When a third qubit was introduced into the experiment, the success rate decreased to only 50% because the computer found it more challenging to maintain control over the environment. This break-through demonstrates how they can easily mimic occurrences that cannot be duplicated in the real world.
Quantum Computers' Future Potential
Uncertainty is usually not looked at in a positive light. However, quantum computers take advantage of superposition and this uncertainty in solving problems in a different manner.
In the healthcare industry, diseases plague millions of people. With the help of these computers and specially designed applications, one can use uncertainty to predict the spread of a particular illness and help to find a cure.
Uncertainty with the IT industry means that you can use this technology to prevent hackers from accessing private information. A hacker would never be able to decode a password key perfectly because they would have to break the laws of quantum physics to break encryption with this technology.
The most shocking aspect is the development of applications for teleporting information with the use of a quantum computer. It is not the teleportation of a physical object, but the transportation of data. This is possible through the manipulation of photon particles across space and time, creating a channel for teleportation, and also making it possible for a new type of internet. Scientists were able to complete this by using entanglement with two twin photon particles, separating them by sending one to a satellite that orbits the earth, and then begin the manipulation of one photon, which in turn also manipulates the other. Why or how this happens is not entirely clear, but it has been accomplished.
Due to the advanced capabilities of this new technology, artificial intelligence is on the verge of reaching an entirely new level. The human brain has always been much more sophisticated and complex than any computer could have been designed. Engineers have been trying to replicate this type of neural network for a long time.
Currently, scientists are building a quantum computer that performs very similar to the human brain. The real challenge with this is designing the software program to accomplish this difficult task and uploading it to a quantum computer. So, the question still remains, will computers be calling all the shots? You tell me.
Larry Slawson from North Carolina on March 19, 2019:
A very interesting idea. I have never heard of this before. Thank you for sharing.


- On Tuesday, Intel delivered something called “a 17-qubit superconducting test chip” to QuTech, Intel’s research partner in the Netherlands.
- This is the world’s second 17-quantum bits, or qubits, quantum computing chip. The first was introduced by IBM in May.
- This chip allows Intel to put a stake in the ground in one of the strangest, and potentially game-changing, new forms of computing that researchers are currently developing.
On Tuesday, Intel came out with its state-of-the 17-qubit superconducting test chip, matching the biggest quantum computer chip ever to be produced, by IBM.
Until now, quantum computing has been, in some regards, a two-horse race between IBM and Google. In April, Google showed off its research on a nine qubit computing chip and has advanced other research that could allow it to break some quantum computing records by the end of the year. In May, IBM showed off the first-ever 17 qubit chip.
IBM’s work is based on research done at Yale through professor Robert Schoelkopf (the IBM team includes many of his Ph.D. and post-grad students). Google’s work is based on research from University of California at Santa Barbara under professor John Martinis, an effort that was backed and absorbed by Google in 2014.
All the researchers from IBM, Intel, Google and elsewhere, like Microsoft, are all in a race to to build a 50 quibit chip. That’s the size needed to build a supercomputer which would be vastly more powerful than any of today’s supercomputers. No one even knows what kinds of problems a computer that fast and smart could solve.
Quantum computers are different than today’s computers, which are digital. A digital computer thinks in two states: zero and one (or off and on). But a quantum computer uses combinations of zeroes and ones to creates multiple states, which can be a zero, a one, both at the same time or (and this is the weird part) something in between, a mysterious zero/one state that’s hard to describe or determine.
These messy states are called “entanglement,” and there are already several well-known mathematical formulas (aka algorithms), that can make use of these states to calculate things that traditional computers aren’t powerful enough yet to do. For instance, quantum computers can work with billions of variables at the same time, like the interaction between molecules in chemistry.
They are also great for machine-learning tasks. These computers are expected to help find new drugs, create new forms of computer security. It is also believed that this type of computing could lead to computers that can think and reason to create humanoid robots, or deliver medicine that is personalised to each human’s own, unique chemistry.
If all this sounds hard to grasp, don’t worry, you aren’t alone. Microsoft is also betting big on quantum computing and yet Bill Gates admits that, despite all the physics and maths he knows, even he doesn’t really understand how quantum works. That’s how complicated it is.
Colder than space
For now, the challenge is simply to build bigger quantum computers.
As Intel explains, qubits are tremendously fragile. Any noise or unintended distraction can cause them to lose data. They rely on superconducting metals that must be kept unbelievably cold. They must operate in a temperature known as “20 millikelvin — or 250 times colder than deep space,” Intel says.
That kind of condition is hard to create and maintain.
It’s not just the cold that’s a problem. As a quantum computer grows in size by adding more qubits, it can malfunction in a lot of ways.
But progress is going fast. In May of 2016, IBM launched a five-qubit machine and the world’s first cloud service. Flash forward a year and these chips are already more than triple the size.
Google expects that it will have created a test computer so big and powerful by the end of this year, that it will be able to perform certain calculations that traditional supercomputers cannot do, a concept called “quantum supremacy,” Martinis told Motherboard.
In the meantime, Intel just threw itself headlong into the game. Here’s a closer look at what it’s up to:
Get the latest IBM stock price here.
Intel's 7-qubit test chip is about the size of a quarter. The gold connectors allow the chip to be connected to the world outside the quantum computer.
Here's a look at the other side of the chip, as it was packaged in the box. One of the things that Intel is also working on is how to eventually mass produce these chips. Mass production is a much bigger, harder problem than creating a single experimental chip.
There are still lots of variables to be perfected before this technology is ready for the factory floor. These researchers at QuTech's quantum computing lab are focused on just that.
Just for comparison: IBM's quantum computer lives in that white thing. It's a special refrigerator that keeps it at almost absolute zero.
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