Scientists may now have found a solution to Stephen Hawking’s famous black hole paradox, which has puzzled experts since the 1970s.
A team of researchers from the University of Sussex, University of Bologna and Michigan State University have published two studies proposing that black holes feature something called “quantum hair,” which allows them to break out of this decades-old conundrum that highlighted possible inconsistencies between Einstein’s general theory of relativity and quantum mechanics.
This new work attempts to better integrate these two systems by utilizing new mathematical formulae developed by researchers during the last decade. If the notion of “quantum hair” does prove true, it would be a significant finding for theoretical physics, while eliminating the need to radically rethink how we see the universe — at least, for now.
“It was generally assumed within the scientific community that resolving this paradox would require a huge paradigm shift in physics, forcing the potential reformulation of either quantum mechanics or general relativity,” said University of Sussex professor of theoretical physics Xavier Calmet in a statement. “What we found — and I think is particularly exciting — is that this isn’t necessary.”
‘Hairy’ Black Holes
According to the laws of quantum mechanics, information that exists in our universe cannot be destroyed, and this conservation of “quantum information” is fundamental to the universe. However, black holes present a challenge to these laws, as black holes are regions of spacetime where gravity is so strong that nothing — not even light — can escape from them. So where does the information that has been sucked into these (supposedly) inescapable black holes go? That question is essentially the crux of Hawking’s black hole information paradox.
The researchers’ first paper, titled “Quantum Hair from Gravity” and recently published in the journal Physical Review Letters, addresses part of this question by showing that there are actually more to black holes than previously thought in classical physics.
Rather than being merely simple objects with a certain mass, speed and rotation, as defined under classical physics’ so-called “no-hair theorem“, the team’s new findings suggest that black holes are actually more complex and ‘hairier’ than general relativity might imagine.
That’s because as matter is sucked into a collapsing black hole, a barely imperceptible imprint — a “quantum hair” — is left in its gravitational field. It is this quantum imprint that is the mechanism for preserving information at the quantum level.
The team used their calculations to compare two theoretical stars that form from different initial chemical compositions, which then collapse into two black holes of the same mass and radii. Working under the notions of classical physics, it would be considered impossible to go back in time to differentiate between the two stars, given the similar final states of the two black holes.
However, the team’s new calculations show that while these two black holes may appear the same on the macroscopic level, they would have slight differences in their gravitational fields on the microscopic, quantum level. Information pointing to what the black holes were initially made of is stored in gravitons, a hypothetical elementary particle that acts as the mediator between the gravitational forces that operate in the field of quantum gravity.
According to the team, it’s quantum gravity that enabled them to discover these discrepancies in the gravitational field — creating a kind of “memory” in the gravitational field of the initial state of the black hole.
“It turns out that black holes are in fact good children, holding onto the memory of the stars that gave birth to them,” said Calmet.
Entangled ‘Quantum Hairs’
The researchers’ second follow-up paper, published separately in Physics Letters B, demonstrates how Hawking’s black hole information paradox is resolved through this mechanism of “quantum hair.” The team’s findings show that classical physics’ previous ideas about black holes’ inescapable event horizon are more complicated when examined more closely under the lens of quantum mechanics.
There are intricate entanglements on the quantum level between the matter that is inside the black hole, and the state of the gravitons outside the black hole. It is this subtle quantum entanglement that makes it possible to “encode” quantum information in the thermal radiation (also known as Hawking radiation) that is emitted from the event horizons of such black holes. Thus, quantum information is shown to be preserved even as a black hole collapses, because Hawking radiation from a black hole is entangled with the quantum state of spacetime itself.
For now, however, it is not possible for the team to empirically test their theory using our current astronomical technology, as such miniscule gravitational fluctuations would evade the tools that are available now. Nevertheless, the team’s findings presents a more consistent way to make calculations for black holes, without having to reinvent both classical and quantum physics.
Image: Aman Pal via Unsplash.


If you want to understand gravity, it makes sense to study black holes. Nowhere else can you find so much gravity so conveniently compacted into such a relatively small space.
In a way, in fact, black holes are nothing but gravity. As Einstein showed, gravity is just the warping of spacetime, and black holes are big spacetime sinks. All the matter falling in gets homogenized into nothingness, leaving behind nothing but warped spacetime geometry.
As black holes swallow more matter, they get bigger, of course. But curiously, it’s the black hole’s surface area, not its volume, that expands in proportion to how much stuff the black hole consumes. In some way, the black hole’s event horizon — the spherical boundary demarcating the points of no return for objects falling in — keeps a record of how much a black hole has eaten. More technically, a black hole’s surface area depends on its entropy, as John Archibald Wheeler’s student Jacob Bekenstein showed in the 1970s.
In the 1990s, other physicists (notably Gerard ’t Hooft and Leonard Susskind) developed this insight further, proposing the “holographic principle”: Information contained in a three-dimensional volume can be completely described by the two-dimensional boundary surrounding it. Just as an ordinary holographic image represents a 3-D scene on a 2-D flat surface, nature itself can store information about the interior of a region of space on the surface enclosing it.
If you think about it, it’s not entirely crazy. There are familiar ways that the information in a 3-D space can be contained on its boundaries. Just imagine a room full of 3-D objects with mirrors on the walls. You can reconstruct everything in the 3-D room from the images on the 2-D mirrors.
In 1995, physicist Juan Maldacena developed the holographic idea further. In essence, he showed that quantum math describing physics in three spatial dimensions without gravity can be equivalent to math describing a four-dimensional space with gravity. (Such an equivalence of two different mathematical descriptions is called a duality.)
Maldacena’s insight suggested that holography might be the key to merging gravity with quantum mechanics. Physicists have sought a way to incorporate gravity into a quantum field theory for decades. If Maldacena is right, then apparently all you need is an extra dimension of space (which is provided naturally in superstring theory). Given an added dimension, spacetime with gravity emerges from the physics described by quantum field theory on its boundary.
Lately this idea has resurfaced in a new context. Some physicists have proposed that gravity has something to with quantum entanglement — the spooky connection between distant particles that befuddled Einstein. And it seems that the holographic duality identified by Maldacena has something to do with the gravity-entanglement connection.
“The emergence of spacetime in the gravity picture is intimately related to the quantum entanglement … in the corresponding conventional quantum system, ” Mark Van Raamsdonk of the University of British Columbia argued in a 2010 paper. “It is fascinating that the intrinsically quantum phenomenon of entanglement appears to be crucial for the emergence of classical spacetime geometry.”
More recent work relates the gravity-entanglement link to mathematical tools called tensors. Describing entanglement in complicated systems of many particles is made easier by using networks of tensors to quantify how multiple particles are entangled. Using tensor networks, physicists have developed algorithms that enable simpler analysis of quantum matter such as superconductors. That work has been going on for years. Newer work with tensor networks has provided insights into how the holographic principle relates entanglement to gravity.
In particular, a formulation of tensor networks called MERA (for multi-scale entanglement renormalization ansatz) seems especially promising with respect to understanding gravity. MERA tensor networks describe patterns of entanglement in certain complicated quantum systems, generating a geometry reminiscent of the extra-dimensional space that Maldacena discussed in his duality. In other words, it’s a real-life realization of the quantum field theory-gravity duality.
“When seen from this perspective, ” writes Orús, “one would say that geometry (and gravity) seems to emerge from local patterns of entanglement in quantum many-body states.” Thus, he points out, the tensor network approach supports the conclusion suggested in previous work by Raamsdonk and others: “Gravitational spacetime emerges from quantum entanglement.”
This link between tensor networks, entanglement and gravity may prove useful in studying the physics of black holes or in investigating the quantum nature of spacetime at very small distances, Orús proposes.
Mathematical details of how tensor networks connect entanglement to the geometry of spacetime are beyond the scope of basic blogging. If you want the whole story of Hilbert space, entanglement renormalization and unitary and isometric tensors, start with Harvard physicist Brian Swingle’s 2012 paper in Physical Review D. (A preprint is available, and a paper with further developments is available here.) Orús has posteda more recent (and more accessible) survey of the field.thinking out of the box thinking outside the box thinking outside the box synonym thinking outside the cage thinking outside the box examples thinking outside of the box is considered thinking outside shed thinking outside the box meaning thinking outside the box quotes thinking over feeling thinking over synonym thinking over feeling meaning thinking over dana glover thinking over meaning thinking over and over again thinking over feeling personality thinking over and over again synonym thinking past tense thinking past the sale thinking past textbook thinking fast and slow audiobook thinking fast and slow summary pdf thinking pro rich thinking pros and cons thinking pro pro thinking definition thinking time pro design thinking pro con critical thinking pro critical thinking pro con since thinking disruptive thinking since 1826 ucl disruptive thinking since 1826 have been thinking since i were thinking or i was thinking thinking through the past thinking through synonym thinking through communication thinking through the past volume 1 thinking through sources thinking through the past volume 2 thinking through sources for ways of the world thinking through grammar thinking thru thru thinking meaning thinking things thru still thinking meaning thinking of you till it hurts john till thinking place thinking of you till it hurts lyrics thinking about something till it happens wishful thinking till svenska thinking of you till svenska what is thinking about thinking called thinking to myself thinking to yourself thinking to much quotes thinking to hard thinking to myself synonym thinking to do thinking towards the future thinking towards thinking towards life maternal thinking towards a politics of peace positive thinking towards life creative thinking towards success wishful thinking towards thinking with literature towards a cognitive criticism thinking under pressure thinking under stress thinking under the influence human communication thinking under the influence example thinking under pressure synonym thinking under fire thinking under fire bion thinking of you underneath the mexican moon thinking until head hurts thinking about something until it happens thinking of you until it hurts does thinking make your head hurt why does my head hurt when thinking can you think so much your head hurts when your head hurts is it your brain thinking up a storm thinking up math thinking up and leading up thinking up meaning thinking up a hurricane thinking versus feeling thinking versus critical thinking thinking vs thought thinking vs doing design thinking via zoom critical thinking via the abstraction ladder thinking with mathematical models answers


How AI and Quantum Could Help Fight Climate Change
Earth Day is the day to celebrate our blue planet. The day to remember that it’s the only home we’ve got.
During his very first days in office, President Joe Biden signed a flurry of climate change-related executive orders. He rejoined the Paris Climate Accord, pledged to double offshore wind-produced energy by 2030 and freeze new oil and gas leases on public lands. All in all, he’s committed himself to an ambitious goal.
Ambitious, yes, but realistic — especially with the help of cutting-edge science and technology. To make it happen though, academia and industry should join forces and change our established, traditional approach to the discovery of new materials. We should accelerate the rate of design of new advanced materials, crucial to create sustainable solutions to climate change.
The good news is, we already have the ingredients to make it happen. They are artificial intelligence and, soon, quantum computing.
Adieu to serendipity
Traditionally, we’ve been discovering new materials either by accident (think graphene) or using a lengthy and expensive trial-and-error process. As part of IBM’s Future of Climate initiative, IBM researchers have now successfully used AI to design new molecules for climate change-related applications much quicker that they would have with the traditional discovery methods.
“We’ve designed molecules that could lead to more efficient polymer membranes to filter off carbon dioxide better than currently used membranes in carbon capture technologies,” says Mathias Steiner of IBM Research Brazil, the lead scientist on the project.
That’s incredibly timely, too. The International Energy Agency (IEA) is forecasting a huge surge in CO2 emissions from energy later this year, when the pandemic finally starts easing off. While total energy emissions in 2020 will be a bit lower than the year before, CO2 emissions will increase by the second largest annual amount on record.
Typically, researchers rely on their knowledge and whatever they can find in published literature to design a molecule, hoping it will have the desired properties. Based on the initial design, they then follow many cycles of synthesis and testing of potential molecules until they create a satisfactory one.
The process often takes months, sometimes years, even with the help of computers to run advanced simulations. The most complex molecule we can simulate today is of the size of pentacene, with 22 electrons and 22 orbitals. Anything more complex, and computers stumble.
But the possibilities for molecular configurations are incredibly vast — there are more possible combinations for a new molecule than there are atoms in the universe. That propels the number of potential new materials to infinity. Equally vast is the ever-surging amount of data. In 2018 alone, about 450,000 new papers were published in the field of material science — impossible for any human to go through in a reasonable amount of time.
Enter artificial intelligence. Just five years ago, AI was mostly good at predicting characteristics of an existing material. Now, researchers are using it more and more to rapidly design brand-new materials with desired properties. “The application of AI to accelerated materials discovery is incredibly exciting and it will allow researchers to be far more efficient in their research,” says Stacey Gifford, a climate scientist at IBM Research.”As new technologies, like quantum computing, expand, the pace of discovery will only increase.”
From digital design to the lab
To design a new polymer for CO2 filtering membranes, Steiner and his team first had to outline the desired properties: permeability, chemical selectivity for specific gases, and durability. Next, an AI sifted through the past knowledge on polymer manufacturing — all the previous research tucked away in patents and publications. Then the researchers used predictive, so-called generative models to create a possible new molecule based on the existing data — a molecule that would make the polymer membrane more efficient in separating CO2.
The next step was to simulate this new molecule and the reactions interactions it should have with its neighbors on a high-performance computing cluster, to confirm that it performed as expected. In the future, a quantum computer could improve on these molecular simulations, but we are not there yet today.
Once everything is tip top with the design, the final step in molecular design is AI-driven lab tests to validate the predictions experimentally and create the actual molecules. This could be done using a tool like RoboRXN. Developed at IBM Research in Zurich, this ‘chemistry lab’ combines AI, a cloud computing platform, and robots to help researchers design and synthesize new molecules anywhere and at any time.
Steiner’s team hasn’t yet turned their digitally validated molecules into real ones, but other IBM researchers have done this last step for a different project. While not related to climate change, that study could help us make greener gadgets. IBM scientists used the same AI-boosted ‘accelerated discovery’ approach to create new molecules called photoacid generators (PAGs), important components of computer chips. The PAGs used today have recently come under enhanced scrutiny from global environmental regulators so the world is in need of more sustainable ones.
Sustainable hybrid cloud and AI
But material design isn’t the only way to help the climate. Another group of IBM researchers is working on making the company’s hybrid cloud more sustainable.
IBM is well-known for its hybrid cloud technology and OpenShift as the unified control plane on- and off- premises. A sustainable hybrid cloud enables companies to transparently assess the carbon footprint of their workloads, and reduce it if necessary. “To quantify and optimize the carbon footprint of cloud workloads, we are developing a carbon quantification and optimization method that attempts to make maximum use of renewable energy,” says the lead researcher on the project, Tamar Eilam. “IBM Research is also working on improving the overall efficiency of AI training by developing more efficient hardware.”
Another team, led by Shantanu Godbole at IBM research India, is using AI to help companies cut their carbon emissions associated with processes such as logistics, transportation, manufacturing, agriculture, and so on.
Meanwhile, IBM researchers led by Kommy Weldemariam are creating an AI to assess potential impacts of climate change on supply chain and infrastructure, from railroad lines to roads, bridges and tunnels. Dubbed the Climate Impact Modelling platform, the technology aims to improve regional climate modelling by bringing the model size down to about one kilometer. “At the moment, most climate models have a fairly low resolution, making it tricky to create accurate predictions,” says Weldemariam.
The researchers use physics-based and AI models to predict, assess and quantify the risks from extreme events — such as floods, wildfires or drought. The models can be integrated into enterprise processes, from the supply chain to the asset and infrastructure management, making it easier for companies to deal with a natural disaster.
While the ongoing research is promising, we are nowhere near the finish line. There is still a lot more to do to develop effective solutions to help our planet. And while Biden’s environmental goals are certainly ambitious, it’s almost certain that new technology will help us meet them.


The Key Device Needed for a Quantum Internet
Advances in quantum information science have brought on the possibility of a quantum internet—networks that carry information via photons in superpositions of states, called qubits, rather than the 0’s and 1’s that today’s networks shuttle from place to place.
In the last decade or so, researchers around the world have taken big steps toward building quantum networks. While many groups have started testing small networks tens of miles in size, major obstacles, including the need to develop a key piece of hardware, lie in the way of larger quantum networks. “There’s still lots of research to be demonstrated,” says Gabriella Carini of Brookhaven National Laboratory, New York, an organizer of a “Quantum Internet Blueprint Workshop” that took place in February. “But if you don’t have a vision, all the pieces won’t talk together.” The workshop was a step toward “establishing a nationwide quantum internet” in the US, an effort that has gained momentum with the National Quantum Initiative Act in 2018 and the recent budget request by the Trump administration to fund plans for a quantum internet.
The appeal of quantum networks lies in both immediately practical applications and potential advances for basic science research. One of the clearest applications is the ability to send secure messages without the threat of eavesdroppers. Because information is encoded with superpositions of states, any interception of a message would make qubits’ wave functions collapse, signaling that the message was intercepted.
Qubits can also encode more information than classical bits, so quantum networks could potentially carry higher densities of information more efficiently. “It’s a fundamentally new way to connect information,” says David Awschalom, a researcher at the University of Chicago and Argonne National Laboratory who is working on a quantum network effort in the Chicago area. Quantum networks could advance developments in remote-sensing technology and telescopes as well as applications that scientists don’t yet realize. A quantum internet could be “another revolution at the same level as the classical internet,” Carini says.
However, the same properties that make quantum networks useful present significant challenges. Ground-based networks, whether classical or quantum, often use optical fibers to direct information from place to place in the form of photons. As photons travel through a network, some will be lost over time as a result of impurities in the fibers, weakening the signal. In classical networks, devices called “repeaters” intermittently detect the signal, amplify it, and send it off again. But for information carried by photons in superpositions of states, or qubits, “it’s not possible to read the signal without perturbing it,” Awschalom says.
The key to long-distance quantum communication, researchers say, is to figure out how to build a “quantum repeater” equivalent to the existing classical one. Without a quantum repeater, a qubit would typically only be able to travel through a few miles or up to about 100 miles of fiber—far too little range for widespread networks.
“This quantum repeater is as important for the field of quantum communication as a quantum computer itself is for the field of quantum computing,” says Eden Figueroa of Stony Brook University, New York, and Brookhaven National Laboratory.
But quantum repeaters are far more complicated than classical repeaters, and no one has made a functional one yet. “I think it will still be a while before it can be a practical technology,” says Jian-Wei Pan of the University of Science and Technology of China. In China, Pan and other researchers have made progress toward quantum networks even without quantum repeaters. One example is a 1200-mile fiber network constructed to connect Beijing and Shanghai. But since it doesn’t have quantum repeaters, this network isn’t fully quantum encrypted from end to end; there are several nodes along the route where the information is decrypted and then encrypted again. These nodes are a “temporary solution,” Pan says, while researchers work to develop quantum repeaters.
Another temporary way around not having quantum repeaters is to employ satellites. Earlier this month, Pan and other researchers in China announced that they were able to use a satellite to transfer a quantum “key” between two ground stations about 700 miles apart.
In the US, researchers are building and testing small quantum networks in locations near Chicago, Boston, and New York. One of these is a fiber network connecting Stony Brook University and Brookhaven National Laboratory that Figueroa’s team has been working on for a couple of years. But even before the inter-campus network, Figueroa and colleagues were working on developing hardware for quantum communication. Researchers in the field have known that quantum repeaters would be necessary for long-distance quantum networks for quite a while, Figueroa says, but the technology to really tackle the problem wasn’t available until recently. “Now we’re getting there, where we can build the first prototypes,” he says. “The goal is, in a few years, to try to really demonstrate a quantum repeater in the field.”
There are still many questions to address before researchers can assess whether a nationwide quantum internet is possible, Figueroa says—like whether they will be able to design quantum repeaters that work well enough outside of the lab and whether it will be feasible to produce a large enough volume of the necessary hardware.
“Those are questions that, right now, don't have an answer,” he says. “And they need to be answered before we can make the claim that this quantum internet can be built.”
–Erika K. Carlson
Erika K. Carlson is a Corresponding Editor for Physics based in New York City.


Within each and every cellphone lies a tiny mechanical heart, beating various billion situations a 2nd. These micromechanical resonators engage in an important job in cellphone communication. Buffeted by the cacophony of radio frequencies in the airwaves, these resonators decide on just the proper frequencies for transmitting and receiving signals in between cellular gadgets.
With the growing importance of these resonators, scientists need to have a trusted and effective way to make certain the devices are functioning adequately. That’s best attained by cautiously researching the acoustic waves that the resonators crank out.
Now, researchers at the Nationwide Institute of Criteria and Engineering (NIST) and their colleagues have designed an instrument to image these acoustic waves in excess of a huge range of frequencies and produce “flicks” of them with unprecedented depth.
The scientists calculated acoustic vibrations as fast as 12 gigahertz (GHz, or billions of cycles for each next) and may be able to extend individuals measurements to 25 GHz, furnishing the needed frequency protection for 5G communications as effectively as for potentially strong long term purposes in quantum information.
The challenge of measuring these acoustic vibrations is likely to raise as 5G networks dominate wi-fi communications, making even tinier acoustic waves.
The new NIST instrument captures these waves in motion by relying on a product known as an optical interferometer. The illumination supply for this interferometer, ordinarily a constant beam of laser mild, is in this scenario a laser that pulses 50 million occasions a next, which is significantly slower than the vibrations becoming calculated.
The laser interferometer compares two pulses of laser mild that travel alongside various paths. 1 pulse travels via a microscope that focuses the laser gentle on a vibrating micromechanical resonator and is then reflected back again. The other pulse acts as a reference, touring alongside a path that is regularly altered so that its length is within a micrometer (one particular millionth of a meter) of the distance traveled by the to start with pulse.
When the two pulses satisfy, the gentle waves from each pulse overlap, generating an interference pattern — a established of darkish and mild fringes wherever the waves cancel or boost a person a different. As subsequent laser pulses enter the interferometer, the interference sample alterations as the microresonator vibrates up and down. From the altering pattern of the fringes, researchers can evaluate the height (amplitude) and section of the vibrations at the area of the laser spot on the micromechanical resonator.
NIST researcher Jason Gorman and his colleagues intentionally chose a reference laser that pulses amongst 20 and 250 moments much more slowly than the frequency at which the micromechanical resonator vibrates. That system enabled the laser pulses illuminating the resonator to, in impact, slow down the acoustic vibrations, related to the way that a strobe light seems to sluggish down dancers in a nightclub.
The slowdown, which converts acoustic vibrations that oscillate at GHz frequencies to megahertz (MHz, hundreds of thousands of cycles for every 2nd), is essential mainly because the light-weight detectors used by the NIST crew function much extra specifically, with much less noise, at these reduce frequencies.
“Moving to lower frequencies removes interference from communication signals usually uncovered at microwave frequencies and enables us to use photodetectors with reduce electrical sound,” explained Gorman.
Just about every pulse lasts only 120 femtoseconds (quadrillionths of a second), providing very exact minute-to-second information on the vibrations. The laser scans across the micromechanical resonator so that the amplitude and phase of the vibrations can be sampled throughout the complete floor of the vibrating unit, producing significant-resolution pictures around a wide assortment of microwave frequencies.
By combining these measurements, averaged in excess of a lot of samples, the researchers can make three-dimensional flicks of a microresonator’s vibrational modes. Two kinds of microresonators were being utilised in the review one particular experienced dimensions of 12 micrometers (millionths of a meter) by 65 micrometers the other measured 75 micrometers on a facet — about the width of a human hair.
Not only can the pictures and motion pictures expose no matter if a micromechanical resonator is running as expected, they can also show trouble regions, these kinds of as sites where by acoustic energy is leaking out of the resonator. The leaks make resonators significantly less productive and lead to loss of info in quantum acoustic devices. By pinpointing problematic areas, the procedure presents researchers the info they need to have to increase resonator style and design.
In the Feb. 4, 2022, version of Mother nature Communications, the researchers reported that they could picture acoustic vibrations that have an amplitude (peak) as tiny as 55 femtometers (quadrillionths of a meter), about just one-5-hundredth the diameter of a hydrogen atom.
More than the earlier ten years, physicists have suggested that micromechanical resonators in this frequency assortment may perhaps also provide to keep fragile quantum information and facts and to transfer the info from 1 section of a quantum computer to an additional.
Creating an imaging procedure that can routinely evaluate micromechanical resonators for these purposes will involve even further investigate. But the existing review is already a milestone in assessing the potential of micromechanical resonators to properly execute at the large frequencies that will be essential for successful conversation and for quantum computing in the in the vicinity of future, Gorman mentioned.


Alternate format: Using encryption to keep your sensitive data secure (ITSAP.40.016) (PDF, 391 KB)
Encryption technologies are used to secure many applications and websites that you use daily. For example, online banking or shopping, email applications, and secure instant messaging use encryption. Encryption technologies secure information while it is in transit (e.g. connecting to a website) and while it is at rest (e.g. stored in encrypted databases). Many up-to-date operating systems, mobile devices, and cloud services offer built-in encryption, but what is encryption? How is it used? And what should you and your organization consider when using it?
What is encryption?
Encryption encodes (or scrambles) information. Encryption protects the confidentiality of information by preventing unauthorized individuals from accessing it.
For example, Alice wants to send Bob a message, and she wants to ensure only he can read it. To keep the information confidential and private, she encrypts the message using a secret key. Once encrypted, this message can only be read by someone who has the secret key to decode it. In this case, Bob has the secret key.
Eve is intentionally trying to intercept the message and read it. However, the message is encrypted, and even if Eve gets a copy of it, she can’t read it without acquiring the secret key.
If an individual accidentally receives a message that includes encrypted information, they will be unable to read the encrypted contents without the key to decrypt the message.
How is encryption used?
Encryption is an important part of cyber security. It is used in a variety of ways to keep data confidential and private, such as in HTTPS websites, secure messaging applications, email services, and virtual private networks. Encryption is used to protect information while it is actively moving from one location to another (i.e. in transit) from sender to receiver. For example, when you connect to your bank’s website using a laptop or a smartphone, the data that is transmitted between your device and the bank’s website is encrypted. Encryption is also used to protect information while it is at rest. For example, when information is stored in an encrypted database, it is stored in an unreadable format. Even if someone gains access to that database, there’s an additional layer of security for the stored information. Encryption is also used to protect personal information that you share with organizations. For example, when you share your personal information (e.g. birthdate, banking or credit card information) with an online retailer, you should make sure they are protecting your information with encryption by using secure browsing.
Many cloud service providers offer encryption to protect your data while you are using cloud based services. These services offer the ability to keep data encrypted when uploading or downloading files, as well as storing the encrypted data to keep it protected while at rest.
When properly implemented, encryption is a mechanism that you and your organization can use to keep data private. Encryption is seamlessly integrated into many applications to provide a secure user experience.
How can I use encryption?
Your organization likely already uses encryption for many applications, such as secure browsing and encrypted messaging applications.
If you access a website with padlock icon and HTTPS in front of the web address, the communication (i.e. the data exchanged between your device and the website’s servers) with the website is encrypted.
To protect your organization’s information and systems, we recommend that you use HTTPS wherever possible. To ensure that users are accessing only HTTPS-supported websites, your organization should implement the web security policy tool HTTP Strict Transport Security (HSTS). HSTS offers additional security by forcing users’ browsers to load HTTPS supported websites and ignore unsecured websites (e.g. HTTP).
Encrypted messaging applications
Most instant messaging applications offer a level of encryption to protect the confidentiality of your information. In some cases, messages are encrypted between your device and the cloud storage used by the messaging service provider. In other cases, the messages are encrypted from your device to the recipient’s device (i.e. end-to-end encryption). When using end-to-end encryption services, not even the messaging service provider can read your encrypted messages.
In deciding which tools to use, you need to consider both the functionality of the service and the security and privacy requirements of your information and activities. For further information, refer to protect how you connect.
Encryption is just one of many security controls necessary to protect the confidentiality of data.
What else should I consider?
Encryption is integrated into many products that are commonly used by individuals and organizations to run daily operations. When choosing a product that uses encryption, we recommend that you choose a product that is certified through the Common Criteria (CC) and the Cryptographic Module Validation Program (CMVP). The CC and the CMVP list cryptographic modules that conform to Federal Information Processing Standards. Although the CC and the CMVP are used to vet products for federal government use, we recommend that everyone uses these certified products.
The CCCS recommends
When choosing a suitable encryption product for your organization, consider the following:
- Evaluate the sensitivity of your information (e.g. personal and proprietary data) to determine where it may be at risk and implement encryption accordingly.
- Choose a vendor that uses standardized encryption algorithms (e.g. CC and CMVP supported modules).
- Review your IT lifecycle management plan and budget to include software and hardware updates for your encryption products.
- Update and patch your systems frequently.
Prepare and plan for the quantum threat to cyber security. For more information, please see Addressing the quantum computing threat to cryptography ITSE.00.017.
Encryption for highly sensitive data
Systems that contain highly sensitive information (e.g. financial, medical, and government institutions) require additional security considerations. Contact us for further guidance on cryptographic solutions for high-sensitivity systems and information: email@example.com.


This is part 3 of a Guide in 6 parts about Artificial Intelligence. The guide covers some of its basic concepts, history and present applications, possible developments in the future, and also its challenges as opportunities.
By Maria Fonseca and Paula Newton
Artificial Intelligence: What is It?
Artificial intelligence is coming up in conversations more and more these days. But do you know what it really is? There are many ideas about artificial intelligence that originated in science fiction films, with artificially intelligent robots going wrong and taking over the world. Yet we are now at the point where machines are becoming able to both talk and think. There are also different terms that are used that can be confusing – such as what is machine learning, deep learning and how are these different from AI. So let’s find out what AI really is, and what the terms mean.
Artificial Intelligence, Machine Learning and Deep Learning
Artificial intelligence is considered to be anything that gives machines intelligence which allows them to reason in the way that humans can. Machine learning is an element of artificial intelligence which is when machines are programmed to learn. This is brought about through the development of algorithms that work to find patterns, trends and insights from data that is input into them to help with decision making. Deep learning is in turn an element of machine learning. This is a particularly innovative and advanced area of artificial intelligence which seeks to try and get machines to both learn and think like people.
Typically, AI is considered to include capabilities such as self-driving cars, military simulations, and the ability to compete at the top levels in strategic games, such as Chess, for example. Generally, AI is categorised into three types:
- human inspired
- humanised artificial intelligence
The first type, analytical AI is considered to be paralleled to cognitive intelligence, where learning from what has already happened can be used to make future decisions and solve problems. Human inspired AI includes this as well as human emotions that are involved in decision making. Meanwhile, humanised AI includes cognitive, emotional and social intelligence, and this requires self-awareness.
There are various areas that artificial intelligence can be programmed to work on. These include reasoning and problem solving, knowledge representation, planning, learning, natural language processing, perception, motion and manipulation and social intelligence, as well as general intelligence. Results have varied in all of these different areas depending on precisely what programmers have been trying not do.
What are the Challenges of AI ?
Concerns have arisen about artificial intelligence and the threat it brings. There is the issue raised at the outset about AI threatening people if it is allowed to continue without being reined in. As well as the fear that has been driven into us by sci-fi about artificial intelligence taking over the world, there are also economic worries. Specifically, artificial intelligence is considered by some to be a threat to work for people, as it already has the capability to perform some mundane and menial jobs that people do. There are concerns that mass unemployment could result from this. Others believe that businesses will be optimised through artificial intelligence, and actually there will still be a need for people, to validate the work that AI does. However, others talk of the idea of a universal basic income to be paid to people to allay the fears of not enough work.
What are the Benefits of AI
Parts of Ai, such as machine learning are beneficial in a number of ways. One of the most important is the fact that programming machines to learn in this way significantly cuts back on the requirement to code them manually to deal with a wide range of possibilities and how the machine should react in each case. There have been significant advances in this area, and examples include efforts to try and prevent disease through machine learning analysing genome sets, having machines diagnose depression through interpreting patterns of speech, and pinpointing people that might commit suicide.
Deep learning is even more complex and capable than this. Deep learning needs to be built within frameworks that are complex, which work on copying the way the human brain works. This is problematic since the way the human brain works is still not entirely understood today. The potential for what deep learning could do is phenomenal, but tremendous computing power is required to deliver such as the one only offered by quantum computing. The idea is to programme the machine to have an adaptable mind, so that it can reason within the programme.
There is a lot more to artificial intelligence than this, but this brief outline of its basic concepts hopefully provides a high-level overview that explains some of the basic elements of artificial intelligence and what it may be able to do.
Paula Newton is a business writer, editor and management consultant with extensive experience writing and consulting for both start-ups and long established companies. She has ten years management and leadership experience gained at BSkyB in London and Viva Travel Guides in Quito, Ecuador, giving her a depth of insight into innovation in international business. With an MBA from the University of Hull and many years of experience running her own business consultancy, Paula’s background allows her to connect with a diverse range of clients, including cutting edge technology and web-based start-ups but also multinationals in need of assistance. Paula has played a defining role in shaping organizational strategy for a wide range of different organizations, including for-profit, NGOs and charities. Paula has also served on the Board of Directors for the South American Explorers Club in Quito, Ecuador.


Quantum teleportation is a well-founded discipline already, taking full advantage of the ‘spooky’ (Einstein’s own word for it) properties of quantum entanglement. For those not already aware of its uses, it’s essential to get Star Trek out of your head from the get-go, this is the transfer of information across vast distances, not people or things.
So far, the principle hasn’t been made to work on anything larger than a molecule.
The base unit that is teleported is known as a qubit, which devotees of quantum computing and teleportation alike will already be well aware of. This is the fundamental particle at the heart of quantum computing, an object that can be read as a one or zero (on or off/true or false) or a superposition of both.
Using the concept of quantum entanglement, whereby a particle is split, and any change made to, or state observed in, one half of this particle will instantaneously be imposed on the other, information can be transferred over vast distances at incredible speeds.
The first proof of the tricksy concept of teleportation came over twenty years ago, in 1998. Since then the distance over which the information has been transferred has steadily increased from a matter of meters to over 100 kilometers, on the Earth’s surface at least, with Chinese scientists sending entangled objects into orbit to see quantum teleportation at a distance of 1400km.
And, in theory, there should be no upper limit on the distance apart in which the sender and receiver elements of the qubit can be placed while still remaining entangled.
So that’s where quantum teleportation stands so far. Now it gets even more complicated and spooky. Teleporting a qutrit is the next step. Like the qubit, it is able to be in a superposition of any of its states, but it is also able to occupy a state of one and two (like the qubit) or three.
This allows for a considerable amount more information to be sent at once. And if a particle with three different states sounds like a tricky thing to create – it is.
In a paper available on arxiv.org (and soon to be in the peer-reviewed journal Physical Review Letters), a research team has demonstrated the ability to create and teleport this new quantum particle.
The researchers took a photon (the fundamental particle of light) and used an arrangement of beam splitters, barium borate crystals, and lasers to split the photon’s path, into three separate but close paths, and thus create a three-part entangled object – their qutrit.
Their teleportation wasn’t flawless, however. They measured twelve different entanglements and received a 75% success rate but, for a first try at creating and teleporting a new quantum object, perfect wasn’t what the researchers were looking for.
Equally, the setup period to generate the qutrit was long and slow, but they remain undaunted. Because, for now, it is enough to prove that qutrit teleportation is possible, not just theoretically but practically.
“Combining previous methods of teleportation of two-particle composite states and multiple degrees of freedom, our work provides a complete toolbox for teleporting a quantum particle intact,” the researchers write, demonstrating that this is just a first step on the road to more practical applications in the future.
The team’s only immediate fear is that they may have been beaten to the punch. A report in Scientific American shows that a rival group, who have yet to have their research peer-reviewed, have also managed to teleport qutrits, although their efforts have only been recorded across 10 quantum states rather than 12.
Quantum teleportation is still an impressive and mysterious area of practical physics. It was initially named in 1993 by Charles Bennett, whose co-authors Asher Peres and William Wootters preferred the less science fiction term ‘telepheresis,’ and used the principle of quantum entanglement, an area of physics that still messes with the minds of many an undergraduate, to create practical applications.
This area of quantum behavior is what had Einstein freaking out so much that he described entanglement as ‘spooky action at a distance’ and feared that it may mean there was something fundamental lacking in our understanding of the quantum realm.
In fact, if it were not for the fact that the received information can only be taken up at the speed of light or less, the changing state brought about by one half of a qubit on the other would seem to break the theory of special relativity. But already we are seeing those bizarre anomalies preparing to be harnessed for everyday practical applications.
Quantum teleportation presents the possibility of an incredible leap forward in encrypted communications, with the potential to even create unhackable networks, where any attempt to break into the code being transmitted would be an attempt to violate the very laws of physics (and, in case you needed telling, those laws definitely can’t be broken, no matter how great your hacking skills).
This is because, in order to preserve the laws of physics, the state change that communicates the information from sender to receiver is destroyed once sent, preserving the fundamental principle in quantum physics known as ‘no-cloning.’
And this is what makes quantum teleportation so useful in encrypting data, since no copies can be made, and since any effort to ‘eavesdrop’ on communication will bring about a quantum state change, instantly revealing the act of eavesdropping. These same fundamental laws are also behind the handling errors which still need to be resolved in quantum computing.
The researchers behind the arxiv paper are certainly optimistic about the breakthrough that their experiment represents.
“We expect that our results will pave the way for quantum technology applications in high dimensions,” they write, “Since teleportation plays a central role in quantum repeaters and quantum networks.”
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Envisioning a future quantum internet
The quantum internet, which connects particles linked together by the principle of quantum entanglement, is like the early days of the classical internet – no one can yet imagine what uses it could have, according to Professor Ronald Hanson, from Delft University of Technology, the Netherlands, whose team was the first to prove that the phenomenon behind it was real.
You are famous for proving that quantum entanglement is real, when, in 2015, you linked two particles that were 1.3 kilometres apart. But the main objective of your work has always been to connect entangled particles into a 'quantum internet.' What could such a network enable us to do?
One of the things that we could do is to generate a key to encode messages using the quantum internet. The security of that key would now be based on this property of entanglement, and this is basically the properties of the laws of physics.
You will get a means of communication whose security is guaranteed by physical laws instead of (by) assumptions that no one is able to hack your code.
That's probably the first real application, but there are many, many more applications that people are thinking about where this idea of entanglement, this invisible link at a distance, could actually be helpful. For example, people have calculated that you can increase the baseline of telescopes by using quantum entanglement. So, two telescopes quite far apart could have better precision than each of them individually would have. You could envision using this quantum internet to create entanglement between atomic clocks in different locations around the world, and this would increase the accuracy of timekeeping locally.
So the quantum internet is primarily a tool for encryption?
There is no quantum internet as of yet. And if you think back to the time when people were developing the classical internet, I don't think anybody was really thinking about the applications that we are using it for right now.
The first real users of the internet were like, "Ok there is a big computer somewhere in one place, and I'm in the other place, and I actually want to use that computer because they are very expensive, so how can I make use of that computer remotely? Well, I need an internet to connect to it."
And now we are using the internet in a totally different way. We are all part of this huge global information highway. And I think some of the same things could happen with the quantum internet. It's very hard right now to imagine what we could do (with it), and I think it is even harder than with the classical internet, because this concept of quantum entanglement is so counterintuitive that it is not easy to use your intuition to find applications for it.
How do you envisage the quantum internet? How would we use it?
I envision that, in the end, when you are using the web most of the time, you are using the classical internet, and when you need some extra feature that requires quantum entanglement, then you are using the parallel quantum infrastructure that is also on the internet to get the functionality that you want to have. So it is not going to be a replacement to the classical internet, but it will be something that is added on top of it.
Back in 2014, you announced that you connected particles three metres apart and 'teleported' information between them. In what sense was this information teleported?
Quantum teleportation is the idea that quantum states—and they contain information of course—disappear on one side and then reappear at the other side. What is interesting is that, since the information does not travel on a physical carrier, it's not encoded in a pulse of light—it does not travel between sender and receiver, so it cannot be intercepted. The information disappears on one side and reappears on the other side.
Quantum teleportation is the most fundamental operation that can be done on the quantum internet. So to get entanglement distributed over long distances, you are actually teleporting the entanglement from one node to the other.
In a classical network, you send your data package, and there is an address contained in that, and the router will read off that information and send it on to the next node. We don't want to do that with these quantum signals. We want to send these quantum signals by teleportation so they don't have to go through the (optical) fibre; they disappear on one side and reappear on the other.
Your work is based on this crazy concept of entanglement. What is your personal opinion of how entanglement works?
What I have learned is to let go of all my intuition when I talk about quantum entanglement. Any analogy you try to make with something in the world that we see around us will fail because it is a quantum concept and we don't really see quantum concepts in our daily lives. So I have given up on trying to have an intuitive explanation of what entanglement is.


Newswise — A study of weakly electric fishes from a remote area of the Brazilian Amazon Basin has not only offered a unique window into how an incredibly rare fish has adapted to life in caves over tens of thousands of years, it has also revealed for the first time that electric fish are able to interact with each other over longer distances than known possible in a way similar to AM radio.
In findings published in the journal Frontiers, researchers have shown how a cave-adapted glass knifefish species of roughly 300 living members (Eigenmannia vicentespelea) has evolved from surface-dwelling relatives (Eigenmannia trilineata) that still live just outside their cave door -- by sacrificing their eyes and pigmentation, but gaining slightly more powerful electric organs that enhance the way they sense prey and communicate in absolute darkness.
The study, which analyzed the fishes' electric-based communication and behavior, has detailed the discovery that weakly electric fishes tap into a special channel for long-distance messaging via changes in the amplitude of electrical signals sent to one another. Researchers have adapted Einstein's famous quote on the theory of quantum entanglement -- "spooky interaction at a distance" -- to describe how the weakly electric fishes perceive these social messages, altering each other's behavior at distances up to several meters apart.
Of the nearly 80 species of cavefish known today to have evolved from surface-dwelling fish, all have developed sensory enhancements of some kind for enduring cave life, commonly adapting over millions of years while losing sensory organs they no longer need in the process.
However, biologists have questioned how weakly electric fishes, which use their electrical senses for navigating the dark and murky conditions of the Amazon River, might also adapt -- either evolving heightened electric senses to see and communicate in absolute darkness, or by powering down their electric fields to save on energetic cost when most caves have few food resources.
"One of the big questions about fish that successfully adapt to living in caves is how they adapt to life without light," said Eric Fortune, lead author of the study and biologist at New Jersey Institute of Technology (NJIT). "My colleagues were split between two groups ... one group that predicted that the electric fields of the cavefish would be weaker due to limited food supplies, and another that bet that the electric fields would be stronger, allowing the fish to use their electric signals to see and talk more clearly in the complete darkness of the cave.
"It seems that using their electric sense to detect prey and communicate with each other is quite valuable to these animals; they have greater electric field strengths. Interestingly, our analysis of their electric fields and movement shows that they can communicate at distances of meters, which is quite a long way for fish that are around 10cm in length."
"Nearly all research of cavefish species until now has been limited to behavioral experiments in labs, and that is why this study is special," said Daphne Soares, NJIT associate professor of biology and co-author on the study. "This is the first time we've been able to continuously monitor the behavior of any cavefish in their natural setting over days. We've gained great insight into their nervous system and specialized adaptations for cave life, but it's just as exciting to learn how sociable and chatty they are with each other ... it's like middle school."
Spooky Interactions & Shocking Adaptations
For the investigation, NJIT and Johns Hopkins researchers teamed with biologist Maria Elina Bichuette from the Federal University of São Carlos, who began studying the two groups of fish nearly two decades ago in the remote São Vicente II Cave system of Central Brazil's Upper Tocantins river basin.
Over several days, the team applied a customized electric fish-tracking technique involving placing electrode grids throughout the fishes' water habitats to record and measure the electric fields generated by each fish, allowing the team to analyze the fishes' movements and electricity-based social interactions.
The researchers were able to track more than 1,000 electrical-based social interactions over 20-minute-long recordings taken from both surface and cavefish populations, discovering hundreds of specialized long-distance exchanges.
"When I began studying these fishes, we could watch behavior associated with these fishes' unique and specialized morphology, but in this project, it was fascinating to apply these new technical approaches to reveal just how complex and refined their communication could be," said Bichuette.
"Basically, our evidence shows that the fishes are talking to each other at distance through electricity using a secret hidden channel, amplitude modulations that emerge through the summation of their electric signals. It is not unlike how an AM radio works, which relies on amplitude modulations of a radio signal." said Fortune.
The recordings also showed that strengths of electric discharges in the cavefish were about 1.5 times greater than those of surface fish despite coming at a cost of up to a quarter of their overall energy budget. The team conducted CT scans of both species, showing that the cavefish also possess relatively larger electric organs than their stream-mates, which could explain the source of the cavefishes' extra electrical power.
Another consequence of trading their eyes and surface life for heightened electrosensory perception is that the cavefish were more social and territorial at all hours. Unlike their freely-foraging surface relatives that sleep during the day and forage at night, the cavefish lacked a day-night cycle.
For now, the discovery of the fishes' AM radio-style distant interactions is noted by Fortune as the first of its kind reported among electric cavefish, though he says similar phenomena is now being reported in some other species as well, recently by researchers in Germany who have observed a form of long-distance electrical communication among a group of fish known as Apteronotus. Fortune says the finding could have implications for the field of neurobiology, where weakly electric fish is a unique and powerful model for exploring the nature of the brain-body connection in other animals including humans.
"Electric fish are great systems for understanding the neural basis of behavior, so we have been studying their brains for decades," said Fortune. "These new data are forcing a reexamination of the neural circuits used for the control of behavior of these fishes."


Optical atomic clocks will likely redefine the international standard for measuring a second in time. They are far more accurate and stable than the current standard, which is based on microwave atomic clocks.
Now, researchers in the United States have figured out how to convert high-performance signals from optical clocks into a microwave signal that can more easily find practical use in modern electronic systems.
Synchronizing modern electronic systems such as the Internet and GPS navigation is currently done using microwave atomic clocks that measure time based on the frequency of natural vibrations of cesium atoms. Those vibrations occur at microwave frequencies that can easily be used in electronic systems.
But newer optical atomic clocks, based on atoms such as ytterbium and strontium, vibrate much faster at higher frequencies and generate optical signals. Such signals must be converted to microwave signals before electronic systems can readily make use of them.
“How do we preserve that timing from this optical to electronic interface?” says Franklyn Quinlan, a lead researcher in the optical frequency measurements group at the U.S. National Institute of Standards and Technology (NIST). “That has been the big piece that really made this new research work.”
By comparing two optical-to-electronic signal generators based on the output of two optical clocks, Quinlan and his colleagues created a 10-gigahertz microwave signal that synchronizes with the ticking of an optical clock. Their highly precise method has an error of just one part in a quintillion (a one followed by 18 zeros). The new development and its implications for scientific research and engineering are described in the 22 May issue of the journal Science.
The improvement comes as many researchers expect the international standard that defines a second in time—the Système International (SI)—to switch over to optical clocks. Today’s cesium-based atomic clocks require a month-long averaging process to achieve the same frequency stability that an optical clock can achieve in seconds.
“Because optical clocks have achieved unprecedented levels of accuracy and stability, linking the frequencies provided by these optical standards with distantly located devices would allow direct calibration of microwave clocks to the future optical SI second,” wrote Anne Curtis, a senior research scientist at the National Physical Laboratory in the United Kingdom, in an accompanying article. Curtis was not involved in the research.
Optical clocks can already be linked together physically through fiber-optic networks, but this approach still limits their usage in many electronic systems. The new achievement by the U.S. research team—with members from NIST, the University of Colorado-Boulder, and the University of Virginia in Charlottesville—could remove such limitations by combining the performance of optical clocks with microwave signals that can travel in areas without a fiber-optic network.
For its demonstration, the team built its own version of an optical frequency comb, a pulsed-laser device that uses very brief light pulses to create a repetition rate that, when converted to frequency numbers, resembles “a comb of evenly spaced frequencies or tones spanning the optical regime,” Curtis explains. Modern optical frequency combs were first developed 20 years ago and have played a starring role in both fundamental research experiments and various technological systems since that time.
By measuring the optical beats between a single comb tone and an unknown optical frequency, researchers knew they should be able to directly link faster optical frequencies to slower microwave frequencies. Doing that required a photodetector developed by researchers at the University of Virginia to carry out the optical-to-microwave conversion and generate an electrical signal. The team also wrote its own software for off-the-shelf digital sampling hardware to help digitize and extract the phase information from the optical clocks.
“The piece that has lagged a bit is the high-fidelity conversion of optical pulses to microwave signals with the optical-to-electrical convertor,” Quinlan says. “So if you have pulses where you know the timing to within a femtosecond (one quadrillionth of a second), how do you convert those photons to electrons while maintaining that level of timing stability? That has taken a lot of effort and work to understand how to do that really well.”
The researchers didn’t quite reach their original benchmark for minimizing the potential instability and errors in the microwave signals synchronized with the optical clocks. But even with the current performance, Quinlan and his colleagues realized: “Okay, great, that'll support current and next-generation optical clocks.”
Curtis describes the improved capability to synchronize microwave signals with optical clock signals as a “paradigm shift” that will impact “fundamental physics, communication, navigation, and microwave engineering.” One of the most immediate applications could involve higher-accuracy Doppler radar systems used in navigation and tracking. A more stable microwave signal can help radar detect even smaller frequency shifts that could, for example, better distinguish slow-moving objects from the background noise of stationary objects.
Future space telescopes based on very-long-baseline interferometry (VLBI) could also benefit from the highly stable microwave signals synchronized with optical clocks. Today’s ground-based VLBI telescopes use receiver devices spread across the globe to detect microwave and millimeter-wave signals and combine them into high-resolution images of cosmic objects such as black holes. A similar VLBI telescope located in space could boost the imaging resolution while avoiding the Earth’s atmospheric distortions that interfere with astronomers’ observations. In that scenario, having optical-clock-level stability to synchronize all the signals received by the VLBI telescope could improve observation time from seconds to hours.
“Essentially you’re collecting signals from multiple receivers and you need to time-stamp those signals to combine them in a meaningful way,” Quinlan says. “Right now the atmosphere distorts the signal enough so that [it] is a limitation rather than the time-stamping from a stable clock, but if you get away from atmospheric distortions, you could do much better and then you can utilize a much more stable clock.”
There is still more work to be done before more electronic systems can take advantage of such optical-to-microwave conversion. For one thing, the sheer size of optical clocks means that nobody should expect a mobile device to have a tiny optical clock inside anytime soon. In the team’s latest research, their optical atomic clock setup occupied a lab table about 32 square feet in size (almost 3 square meters).
“Some of my coauthors on this effort led by Andrew Ludlow at NIST, as well as other folks around the world, are working to make this much more compact and mobile so that we can kind of have optical-clock-level performance on mobile platforms,” Quinlan says.
Another approach that could bypass the need for miniature optical clocks involves figuring out whether microwave transmissions could maintain the stability of the optical clock performance when transmitted across large distances. If this works, stable microwave transmissions could wirelessly synchronize performance across multiple mobile devices.
At the moment, optical clocks can be linked only through either fiber-optic cables or lasers beamed through the air. The latter often becomes ineffective in bad weather. But the team plans to explore the beaming possibility further with microwaves, especially after its initial success and with support from both NIST and the Defense Advanced Research Projects Agency.
“What would be great is if we had a microwave link that basically maintains the stability of the optical signal but can then be transmitted on a microwave carrier that doesn't suffer from rainy days and from dusty conditions,” Quinlan says. “But it's still yet to be determined whether or not such a link could actually maintain the stability of the optical clock on a microwave carrier.”
Jeremy Hsu has been working as a science and technology journalist in New York City since 2008. He has written on subjects as diverse as supercomputing and wearable electronics for IEEE Spectrum. When he’s not trying to wrap his head around the latest quantum computing news for Spectrum, he also contributes to a variety of publications such as Scientific American, Discover, Popular Science, and others. He is a graduate of New York University’s Science, Health & Environmental Reporting Program.


Researchers at the National Institute of Standards and Technology (NIST) have constructed and tested a system that allows commercial electronic components—such as microprocessors on circuit boards—to operate in close proximity with ultra-cold devices employed in quantum information processing. That design allows four times as much data to be output for the same number of connected wires.
In the rising excitement about quantum computing, it can be easy to overlook the physical fact that the data produced by manipulation of quantum bits (qubits) at cryogenic temperatures a few thousandths of a degree above absolute zero still has to be initiated, read out, and stored using conventional electronics, which presently work only at room temperature, several meters away from the qubits. This separation has obstructed development of quantum computing devices that outperform their classical counterparts.
That extra distance between the quantum computing elements and the external electronics requires extra time for signals to travel, which also causes signals to degrade. In addition, each (comparatively very hot) wire needed to connect the electronics to the cryogenic components adds heat, making it hard to maintain the ultracold temperature required for the quantum devices to work.
“If you consider our modern computers, what practically limits their speed is the time it takes information to move around between the CPU and graphics and memory—the physical distances, even though it is moving at the speed of light,” said the project scientist, Joshua Pomeroy. “Those finite distances kill the performance speed. Everything has to be as close as possible so the information gets there fast. So, you need electronics that live with the qubits.”
One obvious way to do that is to place the electronics package inside the cryo environment next to the quantum components. But until now, very few conventional circuit components have been shown to operate properly there. “Moreover, nobody really knows how much energy modern electronics consumes at these temperatures, which is another aspect in addition to just ‘getting something to work,'” Pomeroy said.
To expand circuit functionality at cryogenic temperatures, Pomeroy selected promising standard, commercial electronic chips and constructed a circuit designed to address another problem: The long time required to cool quantum devices, and the restricted number of measurement wires, bottlenecks how many devices can be measured. Since only one device at a time is measured, the new cryo-circuit routes each measurement line to a selected quantum device, “like a railroad switch yard where the track to a distant destination can be connected to many different local destinations, called multiplexing,” Pomeroy said. “In our case, we have 24 measurement lines, each of which can be connected to four different destinations. That requires a lot of switches.”
And all of those switches need to be set correctly. “We need to be able to control the switches (where the train goes) so that we choose which device on the cryo-stage is connected to each of the 24 wires that come out to room temperature,” Pomeroy said. For that task, he employed a standard device from room-temperature electronics: a “shift register” that uses only three control lines but can generate an arbitrarily complex set of control instructions.
“This device uses digital pulses (0 or 1) on the first measurement line that are timed by ‘clock’ pulses from a second wire to build a digital number—for example, 0010—that selects the destination,” Pomeroy said. “In this example, the ‘1’ in the third position would route the measurement to the third device for measurement.” Once the address is set, a pulse on a third control line applies the selected address to the switches, and the measurements can begin.
The system quadruples the amount of measurement data that can be output without adding more wires.
“This work represents a milestone of technical effort that is important for enabling advanced measurement and technology at cryogenic temperatures,” said David Gundlach, chief of NIST’s Nanoscale Device Characterization Division.
“As one additional note,” Pomeroy said, “this entire effort took place during the pandemic shutdown at NIST Gaithersburg. My first (virtual) meeting with our electronics shop staff was in May 2020, and the planning and design continued through winter 2020. Parts and the custom devices were ordered in December and January, with final assembly and bench testing in the spring of 2021. The circuit boards were deployed for mounting and samples for testing in early summer. Since then, they have enabled more than 20 vastly different devices to be measured.”
National Institute of Standards and Technology
Novel design greatly improves output from commercial circuit boards next to superconducting qubits (2022, February 24)
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We might use our computers to play games, browse, watch and work/learn very few times!!. But these machines have far more uses than we think and are being used on a day-to-day basis to solve enormous problems.
Primarily, these types of problems were solved using supercomputers (CPUs, lots of CPUs), but since humans won’t settle for anything lesser, we have invented a more efficient device – Quantum Computers. Don’t get afraid of a few physics terms that will be explained below!!
Need for Quantum Computers
For years, we are relying on classical computers (supercomputers) to solve our problems, and it has been helpful, but not always. The problem with these machines is that they are sequential, and perform calculations one by one. Therefore, a few problems might take a much longer time to get solved and in an inefficient way.
This becomes the primary cause and use case of quantum computers. A problem described by IBM is a great example.
Before we dive into the topic!!
Learning how quantum computers work, requires a basic understanding of a few topics. Not to worry, we have tried to explain them in a simple way.
Superposition is a quantum property, where a particle can exist in any state until it is being measured. A famous example used would be the electrons, who, when unobserved may have any spin, and can define their state only while watching it. A simple explanation for superposition would be the coin toss.
In a classical case, you would flip a coin and be certain that the outcome will be either Heads or Tails. However, superposition would be a state where the coin takes both heads and tails and every other state between them.
Qubits are the basic unit of data in quantum computing. In a classical computer, the basic unit of data would be bits – which is either 0 or 1. Whereas, in quantum computing, qubits are superpositions of 0 and 1 (0 and 1 at the same time). This way, more possibilities of an answer can be calculated within a short span of time.
Entanglement is the simplest to understand than all others. We might have heard this before, “If 2 quantum entangled objects are kept at 2 ends of the universe, and if one particles state is disturbed, it affects the other particle at the other end of the universe”. This property is employed in qubits so that their state can be correlated and can solve more complicated problems (teamwork).
Now, What is Quantum Computing?
Quantum computing is the collective utilization of quantum properties discussed before – superposition, entanglement and so on to solve problems or perform calculations. Theoretically, there are various methods quantum computing can be achieved. The method we currently use is the quantum circuit, which is based on qubits.
After knowing the complexity involved in this, you might think of these computers to be the size of ENIAC, but that’s not the case. These are mostly the size of a refrigerator and are maintained in super cold conditions.
The machine is made to work with the help of Superconductors (super-cooled conductors that offer zero electrical resistance), and employs electrons on them, following a process where the signals are converted into the quantum state, calculations are performed and back into an understandable form.
When scientists found out that there are few problems that aren’t feasible through classical computers, quantum computers was the solution they came to.
Quantum computer finds uses in various domains. With the world now focussing more on AI and Machine learning, these computers speed up the process and also break a few barriers we previously had like the high computational cost for training models and so on.
It also helps in computational chemistry, providing more knowledge in pharmaceutical researches. These can be used in the drug industry, where the current method of development is trial and error which is risky and expensive.
The other fields include quantum cryptography, financial modelling and others.
Are we there yet?
Though we have achieved more in this field in the past decade, we have not reached the peak of its abilities. We have seen most of its use cases, but quantum computers are not the solution for all cases.
For a few scenarios, supercomputers are said to be more useful than quantum computers, and hence we might want to combine those two to create the best machine.
Few companies like Google, IBM, Honeywell, and others are constantly involved in researches regarding this domain. Google AI. along with NASA, has created a 54-qubit quantum processor. IBM has created the first circuit-based commercial quantum computer called IBM Q System One. It has also planned to create a 1000-qubit quantum computer by 2023.
These machines also have downsides. Since it involves super-cold conditions and quantum levels, they are highly sensitive. Heat, electromagnetic fields, and collision with air can cause these qubits to lose their properties and result in system crashes. The more particles involved, the more vulnerable the device becomes.
Therefore, these machines must be kept away from environmental interference and additions qubits are required to correct the errors happening!
Finally, I would say that the present quantum computers may not be the perfect ones we are looking for, but continuous research will lead us to more ideal machines and help our causes.


In a nutshell, multivariable calculus extends the familiar concepts of limits, derivatives, and integrals to functions with more than one independent variable.
Multivariable calculus is much more than just a repeat of single-variable calculus, however. It's a rich subject with its own unique puzzles and surprises.
It introduces new tools that solve important problems in machine learning, neural networks, engineering, quantum computing, and astrophysics, to name just a few.
This course engages you with expertly designed problems, animations, and interactive three-dimensional visualizations all prepared to help you hone your multivariable calculus skills.
This quiz, in particular, sets the stage for our first chapter, which provides a compact introduction to the essential ideas of multivariable calculus.
Vectors play an essential role in multivariable calculus. For now, we can think of vectors as arrows in space, like the one in the 3D interactive below. A vector is defined by its direction and its length (or magnitude).
You have control over the vector's length as well as the two angles and setting the vector's direction. Can you adjust these sliders so that the tip of the arrow sits exactly on the point in space?
Hint: By touch interaction, you can adjust your viewing perspective on the vector and the point. You can also zoom in and out. You might want to consider a perspective where the point is centered in the viewing screen to figure out first.
Later in the course, we'll see that vectors are also collections of numbers, making them ideal building blocks for multivariable functions.
For example, the point in the last problem sits in space and locating it requires three numbers called coordinates. The vector whose tip sits at the point can also be described with these same three numbers!
Looking at the last problem from a different perspective, we can use the two angles specifying the direction of the vector and its length to locate a point in space.
This is the essential idea behind spherical coordinates, a topic covered in detail in Coordinates in 3D.
Calculus truly is the mathematics of limits. Without limits, we couldn't define derivatives or integrals, the two pillars of our subject. This is true no matter how many independent variables we have.
A single-variable limit can often be done with the help of continuity. Mathematically, continuity at a point means Intuitively, it means that the graph of the function has no holes or jumps or breaks.
Later in the course, we'll learn precisely what it means to take a multivariable limit. We'll find continuity to be a huge help in this setting, too.
The graph below represents a function of two variables we'll soon encounter. Use only intuition to determine if this function is continuous everywhere or discontinuous at some points.
The integral was originally designed to solve planar area problems. Similarly, multiple integrals are very useful in solving volume problems in higher dimensions.
We can start thinking about volumes of simple objects in higher dimensions even though we don't know how to integrate in higher dimensions yet or even how to properly visualize them with our 3D minds. We can do this by analogy.
Spheres in dimensions are characterized by a radius. A sphere consists of all points at a fixed distance from a given center. The circle is the lowest dimensional sphere familiar to you. If it has radius its area is Also, the sphere in 3D has volume if it has radius
Arguing by analogy, complete the statement
A sphere of radius in dimensions has volume proportional to
It may seem silly to consider volumes that are more than three-dimensional, but they play important roles in probability and physics where there could be thousands, millions, or even billions of variables.
Mathematically, if on then the area between the graph and the lines is When we generalize to multiple variables, we'll have an integral sign for each new variable, or dimension. For example, the -dimensional sphere has volume If this expression doesn't make sense yet, don't worry: it will soon! The upcoming 3D volumes quiz will set us on the right path by introducing two-variable integrals through the Riemann sum.
One of the greatest applications of calculus (specifically derivatives) is finding the maximum and minimum values of a function.
The upcoming Finding Extreme Values quiz walks us through how this extends to a function with many variables. Before we get there, let's get a sense of what optimizing a function of two variables is like.
Let's say and are any two real numbers that obey the inequality Geometrically, this means that sits inside (or on) the unit circle centered at the origin.
Let's also define the rule which outputs a single number for a pair of input values. For example, Select all of the options that apply to this function if we only consider input satisfying
The example was chosen since it could be optimized without the help of multivariable calculus.
We'll encounter many new problems in our course where algebra and single-variable calculus simply won't be enough. Our next quiz dives deeper into multivariable optimization. There, we'll uncover a powerful new tool and our first truly multivariable concept: the partial derivative.


Princeton researchers have developed a new method that may allow the quick and reliable transfer of quantum information throughout a computing device.
The method, formulated by a team led by Princeton physicist Jason Petta, could eventually allow engineers to design quantum computers consisting of millions of quantum bits, or qubits. So far, quantum researchers have only been able to manipulate small numbers of qubits, which are unfortunately insufficient for use with a practical machine.
“The whole game at this point in quantum computing is trying to build a larger system,” explained Andrew Houck, an assistant professor of electrical engineering who is part of the research team.
To conduct the transfer, Petta’s team used a stream of microwave photons to analyze a pair of electrons trapped in a tiny cage called a quantum dot. The “spin state” of the electrons – information about how they are spinning – serves as the qubit, a basic unit of information. The microwave stream allows the scientists to read that information.
“We create a cavity with mirrors on both ends – but they don’t reflect visible light, they reflect microwave radiation,” said Petta. “Then we send microwaves in one end, and we look at the microwaves as they come out the other end. The microwaves are affected by the spin states of the electrons in the cavity, and we can read that change.”
In an ordinary sense, the distances involved are very small; the entire apparatus operates over a little more than a centimeter. But on the subatomic scale, they are vast. Researchers say this is somewhat akin to coordinating the motion of a top spinning on the moon with another on the surface of the earth.
“[Really], it’s the most amazing thing,” said Jake Taylor, a physicist at the National Institute of Standards and Technology and the Joint Quantum Institute at the University of Maryland. “You have a single electron almost completely changing the properties of an inch-long electrical system.”
For years, teams of scientists have pursued the idea of using quantum mechanics to build a new machine that would revolutionize computing. The goal is not build a faster or more powerful computer, but to construct one that approaches problems in a completely different fashion.
Standard computers store information as classical “bits”, which can take on a value of either 0 or 1. These bits allow programmers to create the complex instructions that are the basis for modern computing power. Since Alan Turing took the first steps toward creating a computer at Princeton in 1936, engineers have created vastly more powerful and complex machines, but this basic binary system has remained unchanged.
The power of a quantum computer originates from the strange rules of quantum mechanics, which describe the universe of subatomic particles. Quantum mechanics says that an electron can spin in one direction, representing a 1, or in another direction, a 0. However, it can also be in something called “superposition” – representing all states between 1 and 0. If scientists and engineers can manage to build a working machine that takes advantage of this, it would open up entirely new fields of computing.
“The point of a quantum computer is not that they can do what a normal computer can do but faster; that’s not what they are,” said Houck. “The quantum computer would allow us to approach problems differently. It would allow us to solve problems that cannot be solved with a normal computer.”
Mathematicians are still working on possible uses for a quantum system, but the machines could allow them to accomplish tasks such as factoring currently unfactorable numbers, breaking codes or predicting the behavior of molecules.
One challenge facing scientists is that the spins of electrons, or any other quantum particles, are incredibly delicate. Any outside influences, whether a wisp of magnetism or glimpse of light, destabilizes the electrons’ spins and introduces errors.
Over the years, scientists have developed techniques to observe spin states without disturbing them. However, analyzing small numbers of spins is still not enough, as millions will be required to make a real quantum processor.
To tackle the problem, Petta’s team combined techniques from two distinct branches of science: from materials science, they used a structure called a quantum dot to hold and analyze electrons’ spins; and from optics, they adopted a microwave channel to transfer the spin information from the dot.
To make the quantum dots, the team isolated a pair of electrons on a small section of material called a “semiconductor nanowire.” Basically, that means a wire that is so thin that it can hold electrons like soda bubbles in a straw. They then created small “cages” along the wire. The cages are set up so that electrons will settle into a particular cage depending on their energy level.
This is how the team reads the spin state: electrons of similar spin will repel, while those of different spins will attract. So the team manipulates the electrons to a certain energy level and then reads their position. If they are in the same cage, they are spinning differently; if they are in different cages, the spins are the same.
The second step is to place this quantum dot inside the microwave channel. This allows the team to transfer the information about the pair’s spin state – the qubit.
Petta says the next step is to increase the reliability of the setup for a single electron pair. After that, the team plans to add more quantum dots to create more qubits. Team members are cautiously optimistic as there appear to be no insurmountable problems at this point in time. However, as with any system, increasing complexity could lead to unforeseen difficulties.
“The methods we are using here are scalable, and we would like to use them in a larger system… But to make use of the scaling, it needs to work a little better. The first step is to make better mirrors for the microwave cavity,” Petta added.