A diverse range of breakthrough technologies, including “artificial leaves” that turn CO2 into fuel, and a technique that harvests water from air, could soon be playing a role in tackling the world’s most pressing challenges, according to a list published today by the World Economic Forum.
The technologies were selected by the World Economic Forum’s Expert Network and Global Future Councils in collaboration with Scientific American and its board of advisors. Each technology was chosen for its potential to improve lives, transform industries and safeguard the planet.
The experts were also looking for indications that the technologies have reached a level of maturity that would enable widespread take-up in the coming three to five years.
“New technologies are redefining industries, blurring traditional boundaries and creating new opportunities on a scale never seen before. Public and private institutions must develop the correct policies, protocols and collaborations to allow such innovation to build a better future, while avoiding the risks that unchecked technological change could pose,” said Murat Sönmez, Head of the Center for the Fourth Industrial Revolution and member of the managing board of the World Economic Forum.
The top 10 technologies to make this year’s list are:
Liquid biopsies mark a step forward in the fight against cancer. First, they are an alternative where traditional tissue-based biopsies are not possible. Second, they provide a full spectrum of information compared to tissue samples, which only reflect the information available in the sample. Lastly, by homing in on circulating-tumor DNA (ctDNA), genetic material that routinely finds its way from cancer cells into the bloodstream, disease progression or resistance to treatment can be spotted much faster than otherwise relying on symptoms or imaging.
Harvesting clean water for air
The ability to extract clean water from air is not new, however existing techniques require high moisture levels and a lot of electricity. This is changing. A team from MIT and University of California, Berkeley has successfully tested a process using porous crystals that convert the water using no energy at all. Another approach, by a start-up called Zero Mass Water from Arizona is able to produce 2-5 litres of water a day based on an off-grid solar system.
Deep learning for visual tasks
Computers are beginning to recognize images better than humans. Thanks to deep learning, an emerging field of artificial intelligence, computer-vision technologies are increasingly being used in applications as diverse as driving autonomous vehicles, medical diagnostics, damage assessment for insurance claims and monitoring of water levels and crop yield.
Liquid fuels from sunshine
Can we mimic the humble leaf to create an artificial photosynthesis to generate and store energy? The prospects are looking increasingly positive. The answer lies in using sunlight-activated catalysts to split water molecules into water and hydrogen, and then using the same hydrogen to convert CO2 into hydrocarbons. Such a closed system – wherein CO2 emitted by combustion is then transformed back into fuel instead of the atmosphere – could prove to be revolutionary for the solar and wind industries.
The human cell atlas
An international collaboration aimed at deciphering the human body, called the Human Cell Atlas, was launched in October 2016. The project, backed by the Chan Zuckerberg Initiative aims to identify every cell type in every tissue; learn exactly which genes, proteins and other molecules are active in each type and the processes which control that activity; determine where the cells are located exactly; how the cells normally interact with one another, and what happens to the body’s functioning when genetic or other aspects of a cell undergo change, among other things. The end product will be an invaluable tool for improving and personalizing health care.
The Fourth Industrial Revolution is providing farmers with a new set of tools to boost crop yield and quality while reducing water and chemical use. Sensors, robots, GPS, mapping tools and data-analytics software are all being used to customize the care that plants need. While the prospect of using drones to capture plant health in real time may be some way off for most of the world’s farmers, low-tech techniques are coming online too. Salah Sukkarieh, of the University of Sydney, for instance, has demonstrated a streamlined, low-cost monitoring system in Indonesia that relies on solar power and cell phones.
Affordable catalysts for green vehicles
Progress is being made on a promising zero-emission technology, the hydrogen-fed fuel cell. Progress to date has been stymied by the high price of catalysts which contain platinum. However, much progress has been made reducing reliance on this rare and expensive metal, and the latest developments involve catalysts that include no platinum, or in some cases no metal at all.
Vaccines based on genes are superior to more conventional ones in a number of ways. They are faster to manufacture for one thing, which is crucial at times of a violent outbreak. Compared to manufacturing proteins in cell cultures or eggs, producing genetic material should also be simpler and less expensive. A genomics-based approach to vaccines also enables more rapid adaptation in the event of a pathogen mutating, and finally allows scientists to identify people who are resistant to a pathogen, isolate the antibodies that provide that protection, and design a gene sequence that will induce a person’s cells to produce those antibodies.
Sustainable design of communities
Applying green construction to multiple buildings at once has the potential to revolutionize the amount of energy and water we consume. Sending locally-generated solar power to a smart microgrid could reduce electricity consumption by half and reduce carbon emissions to zero if a project currently under development at the University of California at Berkeley Goes to plan. Meanwhile, the same project’s plan to re-design water systems so that waste water from toilets and drains is treated and re-used on site, with rainwater diverted to toilets and washers, could cut demand for potable water by 70%.
Quantum computers’ almost limitless potential has only ever been matched by the difficulty and cost of their construction. Which explains why today the small ones that have been built have not yet managed to exceed the power of supercomputers. But progress is being made and in 2016 the technology firm IBM provided the public access to the first quantum computer in the cloud. This has already led to more than 20 academic papers being published using the tool and today more than 50 start-ups and large corporations worldwide are focused on making quantum computing a reality. With such progress behind us, the word on people’s lips now is “Quantum Ready.”


switch promises powerful computers
Technology Research News
At first glance, a switch is a simple concept.
It is either on or off.
Today's computer chips harbor millions of microscopic electrical switches.
These transistors turn on when an electromagnetic field generated by a
control electrode lowers the transistor's resistance to the flow of electrons,
which allows electrical current to flow from one end of the device to
the other. The presence or absence of this flow represents a 1 or a 0
of digital computing.
Circuits that switch light rather than electricity would make for faster
computers, but it's difficult to use a beam of light to turn another light
beam on and off. Light beams usually just pass through each other, especially
if they are relatively weak.
Researchers from the University of Toronto in Canada have figured out
a way to allow beams of individual photons to affect each other, and have
made a device that switches light in a manner similar to the way electrical
transistors switch electrical current.
Photon transistors could pave the way for fast, low-power, all-optical
Extremely low-power switches are also a necessary component of quantum
computers, which use the delicate differences in the states of atoms
and subatomic particles to compute.
The researchers demonstrated the photon switch by shooting two weak beams
of light into a crystal that was simultaneously bombarded by intense laser
light of another wavelength. "The switch allows two beams of light so
weak that they contain at most a single photon, and most often none at
all, to meet up inside a thin optical crystal," said Aephraim Steinberg,
an associate professor of physics at the University of Toronto in Canada.
One of the weird quantum traits of light is that it is simultaneously
a continuous wave and a stream of tiny particles, or photons. Different
colors of light are different wavelengths. Red light, for example, is
around 650 nanometers, or millionths of a millimeter, from crest to trough,
while higher-frequency blue light measures around 450 nanometers.
Lit up by an intense laser beam of blue light that measures half the wavelength
of the weak red beams, the researchers' crystal allows weak beams of red
light to pass through unless they both contain a photon. "The crystal
is transparent to the two weak signal beams except when both beams contain
a photon, in which case the two photons annihilate [each other], and are
prevented from passing. This is the switch effect," said Steinberg.
The red color of the weak beams disappears, turning the switch off, when
each contains a photon because the two photons essentially merge into
one higher-energy photon of blue light, a process known as upconversion,
according to Steinberg. "A single red photon doesn't possess enough energy
to "turn blue" and will therefore be transmitted undisturbed," he said.
"But since any pair of red photons will upconvert, it's as though a single
photon is enough to switch off the path for the other photon."
The switching interaction occurs in a region of the crystal that is about
one tenth of a millimeter across, but the equipment required for the researchers'
prototype includes an inch-long crystal and a six-foot-wide table containing
lasers and detectors. Because the actual switching is purely optical,
it could in theory be miniaturized using techniques that exist today,
The researchers' prototype works about 60 percent of the time, but the
concept could lead to a reliable switch, according to Steinberg.
The researchers' eventual aim is to use the switch in quantum computers,
Steinberg said. "Our hope is that this could be used as a fundamental
logic gate inside quantum computers, whose [potential] uses are still...
being discovered," said Steinberg.
Quantum computers could be much faster than the fastest possible electronic
computers, because they have the potential to examine every possible answer
to a problem at once. "If you know how to ask the computer the right question,
instead of getting the results of just a single calculation, you may find
out something about the results of all possible calculations, something
the classical computer would've had to run exponentially many times to
determine," Steinberg said.
The research is impressive, and "potentially very significant," said Robert
Boyd, a professor of optics at the University of Rochester. "It's been
well-established that a strong beam of light can be used to control another
beam of light. The novel feature of the present approach is that the two
weak beams interact in the presence of a strong beam, which allows the
interaction to be strong even though the control and signal beams are
both weak," he said.
This method has the potential to produce energy-efficient optical switches
that operate with very weak power levels, which would be useful for applications
like telecommunications and optical computing devices, said Boyd.
The switches are potentially useful for quantum computing for similar
reasons. "The signal levels must necessarily be very weak" for quantum
applications, he said.
Although there are many research efforts under way to bring quantum computing
to reality, it is hard to know if and when these fantastically fast computers
will materialize, said Steinberg. "Thousands of people around the world
are working towards the construction of quantum computers and algorithms
for use on them, but none of us knows if a full-scale device will ever
work," he said. "I'd say it's equally likely that we will never see a
quantum computer in our lifetimes, or that people will stumble across
the right architecture for one in the next ten years or so."
Steinberg's research colleagues were Kevin J. Resch and Jeff S. Lundeen.
They published the research in the November 15, 2001 issue of Physical
Review Letters. The research was funded by the Canadian Natural Sciences
and Engineering Research Council, Photonics Research Ontario, the Canada
Fund for Innovation, the Ontario Research and Development Challenge Fund,
and the U.S. Air Force.
Timeline: > 10 years
TRN Categories: Optical Computing, Optoelectronics and Photonics;
Story Type: News
Related Elements: Technical paper, "Nonlinear Optics with
Less Than One Photon," Physical Review Letters, September 17, 2001.
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A Laser-Sharp View of Electron Correlations
The photoelectric effect refers to the emission of electrons from a metal that is injected with light—a phenomenon that was discovered over 100 years ago and explained by Einstein. Today, the effect is the basis for a powerful experimental method known as angle-resolved photoemission spectroscopy (ARPES). This technique uses light to take a “picture” of a material’s electronic energy bands, the structure of which dictates many material properties. Researchers have steadily increased the resolution of these electron pictures by various means, including employing lasers as the light source. Now, using laser-based ARPES, Anna Tamai of the University of Geneva and colleagues provide an unprecedented test of a theory for materials in which electron correlations are strong . The researchers studied the unconventional superconductor, , and determined that correlations enhance a parameter known as spin-orbit coupling (SOC) by a factor of 2—in agreement with the theoretical prediction. Their accurate measurement of SOC may also help physicists resolve a puzzle surrounding the superconducting state of .
has been a font of interesting physics . In 1994, experimentalists discovered that the material becomes superconducting at about 1.5 K. Theorists soon speculated that was unlike other known superconductors. They also conjectured that its “Cooper pairs” of electrons, which carry the superconducting current, had a spin of 1 instead of a spin of 0 , indicating an unusual pairing mechanism. But the type of pairing has been an ongoing subject of debate. Support for the spin-1 picture comes from various early experiments, such as measurements of the superconducting phase, muon spin rotation, and the Kerr effect, whereas a recent nuclear magnetic resonance (NMR) experiment indicates spin-0 pairs . The nature of the pairing is also relevant to the possibility that is a topological superconductor, an exotic phase of interest for a robust form of quantum computing.
is also attractive because its physics, including the pairing mechanism, is affected by interactions (or “correlations”) between the electrons. In fact, the material has become a model system for understanding these effects both experimentally and theoretically. A theory developed specifically for materials with strong correlations, known as dynamical mean-field theory (DMFT), predicts that electrons in enhance the coupling between electron momentum and spin (spin-orbit coupling) [5, 6]. But this predicted enhancement has yet to be tested.
The work by Tamai and co-workers provides the best such test to date . The team investigated electron correlations in using ARPES to measure three energy bands near the Fermi energy. These bands are derived from three of the 4d orbitals of the ruthenium atoms, and their qualitative shape has been measured in previous ARPES experiments. What was harder to see until now was a theoretically predicted separation (in energy and momentum) between the bands. This band “splitting” occurs at the Fermi energy, and it is caused by SOC involving the 4d electrons.
The team determined the Fermi surface and the energy bands of with unprecedented accuracy by using an 11-eV laser light source with an energy resolution of 3 meV and an angular resolution of 0.2°. Compared with earlier ARPES studies, the bands measured by Tamai et al. have narrower widths, making it easier to see the distortions induced by SOC. The group also took steps to suppress contributions from surface states, ensuring that their measured energy bands correspond to “bulk” electrons. (The experiments were performed at 5 K in the “normal” state of .)
The team determined the magnitude of the correlation-enhanced SOC in experimentally by measuring the band splitting. The enhanced SOC is about twice as large as its “bare” value (no correlations), in agreement with the value calculated within DMFT. A separate, direct measurement of the correlation effects comes from comparing the measured bands with three calculations based on density-functional theory (DFT). This computational tool is more standard than DMFT, but it typically applies to materials without strong electron correlations. DFT calculations were performed without SOC, with bare SOC, and with an “effective” SOC that includes an enhancement from electron correlations (Fig. 1). The excellent agreement of the calculation (Fig. 1, right) with the ARPES data provides direct measurement of the enhanced SOC. These tests of DFT and DMFT give weight to the applicability of these approaches to as well as to other materials with multiple d-electron orbitals, strong SOC, and strong electron correlations, such as the iron-based superconductors.
The “cleanliness” of the ARPES data also allowed the authors to confirm a fundamental assumption of DMFT that is related to the determination of so-called electron self-energies. These are shifts in energy that result from electron interactions, and they can have sizable effects on the energy bands. DMFT typically assumes the self-energies are momentum independent to simplify calculations. The researchers confirmed this “ansatz” by extracting self-energies from their measured bands, a result that provides further strength to the applicability of DMFT for .
Beyond testing theory, knowing the strength of the SOC is of interest for understanding superconductivity in —a far from settled topic. Strong SOC could substantially mix the spin-0 and spin-1 states of the Cooper pairs. Figuring out whether the SOC is sufficiently strong for this mixing to occur will require additional calculations . But this step is worth making as physicists try to reconcile the new NMR data , which suggest spin-0 Cooper pairs, with older measurements, which support spin-1 pairs .
This research is published in Physical Review X.
- A. Tamai et al., “High-resolution photoemission on reveals correlation-enhanced effective spin-orbit coupling and dominantly local self-energies,” Phys. Rev. X 9, 021048 (2019).
- A. P. Mackenzie and Y. Maeno, “The superconductivity of and the physics of spin-triplet pairing,” Rev. Mod. Phys. 75, 657 (2003).
- T. M. Rice and M. Sigrist, “: An electronic analogue of ?,” J. Phys. Condens. Matter 7, L643 (1995).
- A. Pustogow et al., “Pronounced drop of NMR Knight shift in superconducting state of ,” arXiv:1904.00047.
- G. Zhang et al., “Fermi Surface of : Spin-orbit and anisotropic Coulomb interaction effects,” Phys. Rev. Lett. 116, 106402 (2016).
- M. Kim et al., “Spin-orbit coupling and electronic correlations in ,” Phys. Rev. Lett. 120, 126401 (2018).
- Q. H. Wang, C. Platt, Y. Yang, C. Honerkamp, F. C. Zhang, W. Hanke, T. M. Rice, and R. Thomale, “Theory of superconductivity in a three-orbital model of ,” Europhys. Lett. 104, 17013 (2013).


Cryptography is a method of protecting information and communications through the use of codes, so that only those for whom the information is intended can read and process it. The prefix “crypt-” means “hidden” or “vault” — and the suffix “-graphy” stands for “writing.”
In computer science, cryptography refers to secure information and communication techniques derived from mathematical concepts and a set of rule-based calculations called algorithms, to transform messages in ways that are hard to decipher. These deterministic algorithms are used for cryptographic key generation, digital signing, verification to protect data privacy, web browsing on the internet, and confidential communications such as credit card transactions and email.
Cryptography is closely related to the disciplines of cryptology and cryptanalysis. It includes techniques such as microdots, merging words with images, and other ways to hide information in storage or transit. However, in today’s computer-centric world, cryptography is most often associated with scrambling plaintext (ordinary text, sometimes referred to as cleartext) into ciphertext (a process called encryption), then back again (known as decryption). Individuals who practice this field are known as cryptographers.
Modern cryptography concerns itself with the following four objectives:
- Confidentiality: the information cannot be understood by anyone for whom it was unintended
- Integrity: the information cannot be altered in storage or transit between sender and intended receiver without the alteration being detected
- Non-repudiation: the creator/sender of the information cannot deny at a later stage his or her intentions in the creation or transmission of the information
- Authentication: the sender and receiver can confirm each other’s identity and the origin/destination of the information
Procedures and protocols that meet some or all of the above criteria are known as cryptosystems. Cryptosystems are often thought to refer only to mathematical procedures and computer programs; however, they also include the regulation of human behavior, such as choosing hard-to-guess passwords, logging off unused systems, and not discussing sensitive procedures with outsiders.
Cryptosystems use a set of procedures known as cryptographic algorithms, or ciphers, to encrypt and decrypt messages to secure communications among computer systems, devices such as smartphones, and applications. A cipher suite uses one algorithm for encryption, another algorithm for message authentication, and another for key exchange. This process, embedded in protocols and written in software that runs on operating systems and networked computer systems, involves public and private key generation for data encryption/decryption, digital signing and verification for message authentication, and key exchange.
Types of cryptography
Single-key or symmetric-key encryption algorithms create a fixed length of bits known as a block cipher with a secret key that the creator/sender uses to encipher data (encryption) and the receiver uses to decipher it. Types of symmetric-key cryptography include the Advanced Encryption Standard (AES), a specification established in November 2001 by the National Institute of Standards and Technology as a Federal Information Processing Standard (FIPS 197), to protect sensitive information. The standard is mandated by the U.S. government and widely used in the private sector.
In June 2003, AES was approved by the U.S. government for classified information. It is a royalty-free specification implemented in software and hardware worldwide. AES is the successor to the Data Encryption Standard (DES) and DES3. It uses longer key lengths (128-bit, 192-bit, 256-bit) to prevent brute force and other attacks.
Public-key or asymmetric-key encryption algorithms use a pair of keys, a public key associated with the creator/sender for encrypting messages and a private key that only the originator knows (unless it is exposed or they decide to share it) for decrypting that information. The types of public-key cryptography include RSA, used widely on the internet; Elliptic Curve Digital Signature Algorithm (ECDSA) used by Bitcoin; Digital Signature Algorithm (DSA) adopted as a Federal Information Processing Standard for digital signatures by NIST in FIPS 186-4; and Diffie-Hellman key exchange.
To maintain data integrity in cryptography, hash functions, which return a deterministic output from an input value, are used to map data to a fixed data size. Types of cryptographic hash functions include SHA-1 (Secure Hash Algorithm 1), SHA-2 and SHA-3.
Attackers can bypass cryptography, hack into computers that are responsible for data encryption and decryption, and exploit weak implementations, such as the use of default keys. However, cryptography makes it harder for attackers to access messages and data protected by encryption algorithms.
Growing concerns about the processing power of quantum computing to break current cryptography encryption standards led the National Institute of Standards and Technology (NIST) to put out a call for papers among the mathematical and science community in 2016 for new public key cryptography standards. Unlike today’s computer systems, quantum computing uses quantum bits (qubits) that can represent both 0s and 1s, and therefore perform two calculations at once. While a large-scale quantum computer may not be built in the next decade, the existing infrastructure requires standardization of publicly known and understood algorithms that offer a secure approach, according to NIST. The deadline for submissions was in November 2017, analysis of the proposals is expected to take three to five years.
History of cryptography
The word “cryptography” is derived from the Greek kryptos, meaning hidden. The origin of cryptography is usually dated from about 2000 B.C., with the Egyptian practice of hieroglyphics. These consisted of complex pictograms, the full meaning of which was only known to an elite few. The first known use of a modern cipher was by Julius Caesar (100 B.C. to 44 B.C.), who did not trust his messengers when communicating with his governors and officers. For this reason, he created a system in which each character in his messages was replaced by a character three positions ahead of it in the Roman alphabet.
In recent times, cryptography has turned into a battleground of some of the world’s best mathematicians and computer scientists. The ability to securely store and transfer sensitive information has proved a critical factor in success in war and business.
Because governments do not wish certain entities in and out of their countries to have access to ways to receive and send hidden information that may be a threat to national interests, cryptography has been subject to various restrictions in many countries, ranging from limitations of the usage and export of software to the public dissemination of mathematical concepts that could be used to develop cryptosystems. However, the internet has allowed the spread of powerful programs and, more importantly, the underlying techniques of cryptography, so that today many of the most advanced cryptosystems and ideas are now in the public domain.
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reads quantum bits
Technology Research News
The key to quantum computing is being able
to use the spins of subatomic particles such as electrons to represent
the ones and zeros of computing. A particle can be spin-up or spin-down
in a way similar to a top spinning either clockwise or counterclockwise.
If you could reliably distinguish between spin-up and spin-down energy
in large numbers of particles, the spin possibilities in each particle
could serve as a quantum bit, or qubit,
representing a one or a zero, and you could build a fantastically powerful
computer in very little space.
The trouble is, it's difficult to measure spin. Scientists have done so
by trapping isolated atoms and using lasers to measure spin states, but
they are still a long way from being able to read the millions of quantum
bits required to form a practical quantum computer.
Researchers at the University of California at Berkeley have taken a step
towards that goal by showing that it is possible to measure the spin of
a quantum state of an electron in a nickel atom embedded in a copper oxide
crystal. The development has the potential to make a promising quantum
scheme considerably more practical.
There are four major problems to be solved in making a quantum computer:
its qubits must be able to represent a one or zero long enough for the
computer to perform logic operations on them; the qubits must be able
to interact with each other to carry out those operations; there must
be some way to read the information contained in a qubit in order to see
the results of the operations; and the system must contain a lot of qubits
to do useful computing.
By measuring the spin of a single atom, the Berkeley researchers have
found a way to read the information contained in a certain type of qubit.
This type of qubit -- a single atom embedded in a solid made of other
atoms -- has already shown potential for solving the other three problems
associated with quantum computing.
A theoretical proposal by University of Maryland researcher Bruce Kane
shows that qubits made from phosphorus atoms embedded in silicon could
hold their spin states for a long enough time to do computing, could be
placed closely enough to interact with each other, and could be made in
a large quantity.
The Berkeley method addresses the key missing piece in that plan by showing
that it is possible to measure the spin of a single electron within an
impurity, or atom of one material embedded in another.
The researchers used a scanning tunneling microscope (STM) to measure
the spin of an electron associated with a nickel impurity embedded in
copper oxide, but they had to make some modifications to do so.
Scanning tunneling microscopes use tips that resemble needles, but are
so sharp that they taper to a single atom. The tip hovers over the surface
of a material and maps the changes the material's electron energy makes
to the electron current flowing through the tip similar to the way a seismograph
Because spin-up and spin-down states have different energy, the researchers
were able to distinguish between them. "We are trying to get an electron
to jump into one of the quantum states from a nearby metal tip. The spin-down
state exists at a lower energy than the spin-up state at the atom we studied,
so by measuring the rate at which the electrons jump into the state as
a function of their energy we can tell which is which," said Davis.
To make the scheme work, however, the researchers had to solve a pair
First, the spin energy of an electron can only be split into discernible
spin-up or spin-down states under certain conditions, said Davis. "In
each [impurity] atom there's a single wave function of the electron...
you can split that wave function into a spin-up and spin-down state if
you're in a high magnetic field at low temperatures," he said.
The amount by which the two energy levels are split is proportional to
the strength of the magnetic field, so the stronger the magnetic field,
the easier it is to distinguish the two levels.
Second, heat energy easily drowns out spin energy. "The amount of energy
associated with the temperature has to be smaller than the splitting between
the two levels [otherwise] thermal energy would just be knocking electrons
up and down from the bottom [energy level] to the top one all the time,"
The researchers solved the problems by measuring electron spin in a nickel
impurity embedded in a superconductor at a relatively low temperature.
Copper oxide is a high-temperature superconductor, meaning its electrons
are free to travel without resistance at 85 degrees Kelvin, or -188 degrees
Celsius, which, though very cold, is less cold than the temperatures of
4 degrees Kelvin, or -269 degrees Celsius required by low-temperature
Because nickel is magnetic, it exerts a magnetic force that is very strong
at distances of 10 or 20 nanometers away from the atom. "The effective
field at the nickel atom is hundreds of Tesla. So we didn't need a big
external magnet, we got it for free by putting a magnetic atom into the
solid," said Davis.
The researchers next plan to use the same technique to measure electron
spin in a phosphorus atom embedded in a silicon chip, which is the setup
required in the Kane quantum computer proposal.
Because phosphorus is not magnetic, the Berkeley researchers need to generate
a large magnetic field in order to measure the spins of its quantum particles.
The researchers are planning to build an STM that can generate an eight
Tesla field at temperatures as low as 20 millikelvin in order to carry
out the measurements, said Davis.
If the researchers are able to measure spin states in phosphorus atoms,
"then that's really big news because that was the really big problem of
the Kane proposal," said Paul Kwiat, a physics professor at the University
of Illinois at Urbana-Champaign.
"The main reason people were skeptical about [the Kane proposal] was the
need for reading out single spins, which seemed like it was not going
to be very easy, and it still may not be very easy. But certainly this
is an experiment in the right direction," Kwiat said.
The Kane proposal is probably the most promising model so far for quantum
computing, largely because it is based on silicon, Kwiat added. "If you
can do something in silicon... and you get it to work, you can hand it
to the silicon industry," he said.
Researchers in the quantum field generally agree that practical quantum
computers are at least two decades away, if they can be built at all.
"It's like asking when fusion will generate cheap energy. It's a possible
but technically hard challenge," said Davis.
Davis' research colleagues were Eric W. Hudson of the University of California
at Berkeley and the National Institute of Standards and Technology, Christine
M. Lang and Vidya Madhavan of the University of California at Berkeley,
Shuheng H. Pan of the University of California at Berkeley and Boston
University, Hiroshi Eisaki from the University of Tokyo in Japan and Stanford
University, and Shin-ichi Uchida of the University of Tokyo.
They published the research in the June 21, 2001 issue of the journal
Nature. The research was funded by the Office of Naval Research (ONR)
and the Department of Energy (DOE).
Timeline: > 20 years
TRN Categories: Quantum Computing
Story Type: News
Related Elements: Technical paper, "Interplay of Magnesium
and High Tc Superconductivity at individual Ni impurity atoms in Bi2Sr2CaCu2O8+
d," Nature, June 21, 2000; Additional images at the Davis group website:
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QUANTUM INFORMATION PROCESSING
Entanglement is central to the phenomenon of quantum teleportation. It is the process by which quantum information (e.g. the exact state of an atom or photon) is transmitted, exactly, using classical communication channel from one location to another, with the help of previously shared quantum entanglement between the sending and receiving locations.
Anybody who has watched Star-Trek is familiar with the idea of teleportation where an object or person is made to “disappear” in one place while a perfect replica emerges somewhere else (“apparate” for Harry Potter fans). The science behind teleportation is usually not explained by science fiction writers, but the effect they portray is dramatic. Information from the original object is “extracted” and transmitted to the receiving end which is then used to construct the replica. The replica does not contain actual material of the original, but is invariably created from the same kinds of atoms, their arrangement modeled in exactly in the same way as the original. Think of a fax machine that works on 3-dimensional objects as well as documents, but produces an exact copy instead of an approximate facsimile, destroying the original during the process of “scanning”.
Quantum teleportation is a much more realistic and subtler effect where information is transferred between entangled quantum states. The idea of teleporting quantum particles emerged from purely theoretical considerations of a young researcher named William Wootters, who, in 1980, wrote his Ph.D. thesis centered on the question: from what principles can Born’s rule in quantum theory be derived? Important to his considerations was a task known as quantum state tomography. Since measurement of a quantum state results in its modification, obtaining a complete characterization of a quantum state requires measurements on many identical copies of itself. Quantum state tomography is the process by which a quantum state is reconstructed using measurements on an ensemble of identical quantum states. In the fall of 1989, Asher Peres found strong numerical evidence showing joint measurements on a pair of systems yielded superior tomography than the separate measurements. It seemed, therefore, that if a pair of similarly prepared particles was separated in space, an experimenter would be less likely to identify their state than if they were together. After attending a seminar delivered by Wootters in 1992, Charlie Bennett of IBM Research Division, T.J. Watson Research Center, started to ponder whether the inherent nonlocality associated with spatially separated entangled systems could achieve the same quality of quantum state tomography as opposed to the case when they were in contact.
In 1993, Bennett and an international group of six scientists including Wootters, showed that the quantum state of a system could indeed be transferred from one party to distant party using only local operations and classical communication, provided the original is destroyed, and in so doing were able to circumvent the no-cloning theorem. The trick was dubbed “quantum teleportation” by its authors. The abstract of their paper, published in Physical Review Letters reads: “An unknown quantum state can be disassembled into, then later reconstructed from, purely classical information and purely nonclassical Einstein-Podolsky-Rosen (EPR) correlations. To do so the sender Alice, and the receiver Bob, must prearrange the sharing of an EPR-correlated pair of particles. Alice makes a joint measurement on her EPR particle and the unknown quantum system, and sends the classical result of this measurement. Knowing this, Bob can convert the state of his EPR particle into an exact replica of the unknown state which Alice destroyed.”
In a conventional facsimile transmission, the original object is practically unscathed after the scanning process is complete, although scanning in this case is capable of extracting only partial information about the object. The scanned information is then transmitted to the receiving station, where it is imprinted on paper (or on some other surface) to produce an approximate copy of the original. In contrast, two entangled objects B and C (Figure 12) that were originally in contact, are separated in quantum teleportation—object B is brought to the sending station, while object C is transmitted to the receiving station. A, the original object to be teleported, is scanned together with object B at the sending station. This process is irreversible as it disrupts the states of both A and B. The scanned information is accepted by the receiving station, where it is used to “select one of several treatments” to be applied to object C. This makes C as an exact replica of A. The information is considered teleported because the original object A never travels the distance between the two locations.
In subsequent years, various groups have demonstrated teleportation experimentally in a variety of systems, including single photons, coherent light fields, nuclear spins, and trapped ions. Quantum teleportation has the immense promise as it can facilitate long range quantum communications. One day it could also be the enabling technology for a “quantum internet”.
In 2014, physicists from the Kavli Institute of Nanoscience at the Delft University of Technology in the Netherlands, reported successful transmission of quantum data involving the spin state of an electron to another electron about 10 feet away (Figure 13). Successful experiments with quantum teleportation has been reported in the past, but the results of the Delft University study have an unprecedented replication rate of 100 percent for their studied distance.
In 2016, researchers at the National Institute of Standards and Technology (Valivarthi, et al., 2016) were able to teleport quantum information carried by photons over 6.2 kilometers (km) of optical fiber, four times farther than the previous record. The researchers used a variation of the method described above: here three observers participate rather than the conventional two. Bob and Alice each make measurements of an entangled state and another photon, about 8 kilometers from each other. Their results are then sent to Charlie, who combines the two results to achieve quantum teleportation. This method assures that the experiment extended beyond a single lab location, and it was done using existing dark fiber and wavelengths of light commonly used in current fiber internet.


In what has been hailed as a computing milestone, a team of researchers from the University of Science and Technology of China has achieved quantum supremacy thanks to a device that can manipulate tiny particles of light.
Dubbed Jiuzhang, the system performed a quantum computation called "Gaussian boson sampling", which has been shown to be intractable for classical computers. Quantum supremacy is achieved when a quantum device is proven to be able to carry out a task that a classical computer would find impossible, or take too long to complete.
While Jiuzhang achieved Gaussian boson sampling in just 200 seconds, the researchers estimated that the same calculation would take the world's fastest supercomputer, Fugaku, 600 million years to complete.
Quantum supremacy has only been claimed once before. Last year, Google's researchers showed off a 54-qubit processor that they said could run a test computation in 200 seconds – a calculation that, according to the research, would take the world's biggest supercomputers 10,000 years to complete.
Qubits come with unprecedented computational power due to their ability to exist in a dual quantum state, and therefore to carry out many calculations at one. Researchers expect that, armed with enough stable qubits, quantum computers will shake up industries ranging from AI to finance through transportation and supply-chains.
The crux of the challenge consists of creating and maintaining enough qubits to make a quantum computer useful, and there are different ways to do so. The quantum technology developed by Google, for example, is entirely different from Jiuzhang's set up: the search giant, for its part, is investing in metal-based superconducting qubits.
This is also IBM's preferred quantum technique, and both tech giants have poured large sums of money into superconducting circuits to push quantum computing research.
For superconducting qubits to remain controllable, however, they need to be kept in very cold temperatures – colder than in deep space. Needless to say, making this practical is still a significant barrier. The extreme sensitivity of qubits to their external environment also means that it is hard to scale up the devices.
Instead of particles of metal, Jiuzhang manipulates photons. The device was built specifically for the quantum task that it carried out, Gaussian boson sampling, which consists of simulating and predicting the erratic behavior of photons.
The task consists of injecting particles of light into a network of beam splitters and mirrors that give photons multiple choices of paths to travel through before reaching different output ports. Photons, however, come with strange quantum properties that complicate the matter: there is no way of knowing deterministically which way they will choose. What's more, if two identical photons hit the beam splitter at exactly the same time, they will stick together and both travel the same randomly-chosen path.
All of this makes it very difficult for classical computers to identify patterns of photon behavior, and to predict the output configuration of photons based on how the particles were input. The difficulty of the calculation also exponentially increases as more photons get involved, which means that a Gaussian boson sampling device is difficult to scale up.
Christine Silberhorn, professor of integrated quantum optics at Paderborn University in Germany, has been working on Gaussian boson sampling for many years. "The scheme has its own challenges," she tells ZDNet. "Scaling up the system is hard, because all components have to be engineered for a quantum experiment, and they have to work accurately together. Moreover, it requires the detections and processing of very large datasets."
The researchers equipped Jiuzhang with 300 beam splitters and 75 mirrors, and said that they managed to measure up to 76 photons during their experiments – enough particles of light to make the calculation intractable for a classical computer.
Cracking the Gaussian boson sampling equation has limited usefulness. For now, in fact, the experiment has done little more than show that Jiuzhang is better than classical computers at solving one very specific task – simulating the unpredictable behavior of photons. That doesn't mean, however, that a large-scale quantum computer will be built anytime soon to solve real-life problems.
The value of the experiment rather lies in the proof that light-based quantum computers might be just as promising as their matter-based counterparts, which so far, courtesy of big tech's interest, have grabbed most of the headlines. "This experiment is an important milestone experiment for quantum simulations based on linear optical systems," says Silberhorn. "It demonstrates the high potential for scalable quantum computation using photons."
Researchers have recently taken interest in photonic quantum computers because of the potential that particles of light have to remain stable even in uncontrolled environments. Unlike devices based on superconducting qubits, photons don't require extreme refrigeration, and could in theory scale up much faster.
"The Boson sampling experiment reported by the USTC group is a real tour de force, and illustrates the potential of photonics as a quantum technology platform," Ian Walmsley, chair in experimental physics at Imperial College London, told ZDNet. "This is a real step forward in developing technologies that harness the power of quantum physics to perform tasks that that are not possible using current technologies."
The new milestone achieved by the team at the University of Science and Technology of China, therefore, is likely to bring new impetus to the on-going race to build up quantum technologies. Google and IBM are only two examples of deep-pocketed players who have shown interest in developing quantum computers, and a rich ecosystem is growing at pace to bring new innovations to the space.
In addition to industry players, nation states have shown strong interest in developing quantum technologies. The Chinese government, for one, is investing heavily in the field. In fact, Jian-Wei Pan, who led the research team that worked on Jiuzhang, was also behind a recent quantum cryptography breakthrough that achieved quantum key distribution over a record-breaking 745 miles.


This morning, Google scientists confirmed in a blog post that their quantum computer had needed just 200 seconds to solve a problem that they claim would take the world’s fastest supercomputer 10,000 years to complete.
The team first ran the algorithm last spring using a 54-qubit processor called “Sycamore.” While the achievement is called quantum supremacy, it doesn’t mean that quantum computers are suddenly more capable than classical computers, since Google’s quantum computer only beat the competition at a single, highly contrived problem. Quantum computers with day-to-day applications may still be decades away, but this is an important scientific milestone when comparing quantum computers to their classical counterpart.
“For such large-scale endeavors it is good engineering practice to formulate decisive short-term goals that demonstrate whether the designs are going in the right direction,” Google’s John Martinis and Sergio Boxio, chief scientists of quantum hardware and quantum computing theory, wrote in the blog post. “So, we devised an experiment as an important milestone to help answer these questions.”
Quantum computers are a new kind of computing device that could one day be capable of solving problems that classical computers can’t. Instead of series of transistors linked together, representing two-choice bits like in classical computers, their base unit is the quantum bit, or qubit, a piece of hardware that mimics the behavior of a subatomic particle. Qubits communicate via the probability-driven theory of quantum mechanics instead of the regular rules of logic. They’re still two-choice systems that output binary code, but getting to the answer incorporates the quantum mathematical ideas of entanglement, superposition, and interference. This new architecture may one day excel at simulating the behavior of subatomic particles well enough to create new medicines and new materials. It might also be able to crack the code that modern-day encryption is based on.
Scientists must first find a physical system that assumes quantum properties. But quantum states are incredibly fragile—the slightest bump of heat or vibrational energy can make initialized qubits lose their quantumness and turn into regular bits. Google’s engineers built theirs from loops superconducting wire, controlled by quick, customized microwave pulses.
Google’s quantum supremacy experiment essentially sets up random circuits out of these qubits. Certain outputs become more common than others. It’s easy for Sycamore to find these outputted strings, but with each new qubit, it would take a regular supercomputer exponentially more time to come up with an answer. Google’s scientists ran the experiment repeatedly, incorporating a new qubit until the supercomputer simulating the quantum computer couldn’t keep up, according to the paper published in Nature.
The main application of such an experiment is that it can produce truly random numbers, something useful in various fields of science, cryptography, art, and of course, online gambling. But a hypothesis called the Church-Turing thesis claims that a theoretical computer called the Turing machine, which basically simplifies all computers to symbols on tape, is the most efficient way to solve computer problems. Google’s quantum computer provides evidence against this thesis.
Rumors and hype have surrounded the Google quantum supremacy announcement since the team published a paper describing how they’d achieve the milestone on the arXiv physics preprint server in 2016. Last month, the Financial Times reported that it had found the Google paper describing the completed quantum supremacy experiment on a NASA server, but Google would not confirm the veracity of the report until today.
Already, scientists are debating whether the quantum supremacy experiment actually demonstrates what it claims. On Monday, the IBM quantum team published a blog post arguing that a classical computer could more accurately run the Google problem in just 2.5 days. Simply put, it’s hard to prove a claim that a classical computer can’t do something.
Regardless, this experiment does not mean that quantum computers are suddenly going to appear in your iPhone; there’s a lot of work left. John Preskill, the CalTech physicist who coined the term quantum supremacy, told Gizmodo in March that while it’s certainly worth pursuing these supremacy experiments, “I think it’s more important to try and develop the tools that we need to scale up further: perfecting error-correction methods, improving the qubits, and addressing the system’s engineering issues that you need to control the platform with thousands or millions of qubits.”
It’s clear that we’ve entered a new era of quantum computing (it’s called the NISQ era), as companies now have noisy but functional devices that may actually be useful soon.
I’m at Google’s lab at Santa Barbara, California today to get a first look at the device. I’ll report back with more images of the computer and what it’s actually like.


A new project will use the electric field in an accelerator cavity to try to levitate a tiny metallic particle, allowing it to store quantum information.
Quantum computing could solve problems that are difficult for traditional computer systems. It may seem like magic. One step toward achieving quantum computing even resembles a magician’s trick: levitation. A new project at the U.S. Department of Energy’s Thomas Jefferson National Accelerator Facility will attempt this trick by levitating a microscopic particle in a superconducting radiofrequency (SRF) cavity to observe quantum phenomena.
Typically at Jefferson Lab and other particle accelerator facilities, SRF cavities enable studies of the atom’s nucleus. They do this by accelerating subatomic particles, such as electrons. This project will use the same type of cavity to instead levitate a microscopic particle of metal, between 1 and 100 micrometers in diameter, with the cavity’s electric field.
“No one has ever intentionally suspended a particle in an electric field in a vacuum using SRF cavities,” said Drew Weisenberger, a principal investigator on this project, as well as Chief Technology Officer and head of the Radiation Detector and Imaging Group in the Experimental Nuclear Physics Division at Jefferson Lab.
If the project team is able to levitate a particle, they might be able to then impart a quantum state on it by cooling the trapped particle to its lowest possible energy level (because that’s when quantum properties occur).
“Storing quantum information on a levitated nanoparticle is our ultimate goal, but for now, it is a proof of principle experiment,” said Pashupati Dhakal, another principal investigator on the project and a staff scientist at Jefferson Lab in the Accelerator Operations, Research and Development Division. “We want to know if we can trap and levitate particles inside the cavity using the electric field.”
Exploring the Quantum with Accelerator Cavities
The idea for this project came from observations of accelerator experts. They think they have already unintentionally levitated unwanted and rare nanoparticles of metal, such as niobium and iron, inside SRF cavities during particle accelerator operations. They suspect that this unintentional levitation has impacted the performance of SRF cavity components.
Researchers are attempting to use a several-decades-old technique called “laser trapping”, as a step toward reliably imparting a quantum state on a particle suspended in a laser beam. But, the Jefferson Lab project team thinks that SRF cavities may provide a better tool for those researchers.
“An electric field could go potentially beyond the capabilities of laser trapping,” Weisenberger said.
Intrinsic characteristics of SRF cavities will overcome some limits of laser trapping. A levitated particle in an SRF cavity that is under vacuum and chilled to super cold temperatures will only interact with the cavity’s electric field and not lose information to the outside, which is important for maintaining a quantum state.
“Like storing information on a computer chip, the quantum state will stay and not dissipate,” Weisenberger said. “And that could eventually lead to applications in quantum computing and quantum communications.”
This project, titled “SRF Levitation and Trapping of Nanoparticles Experiment,” is funded by the Laboratory Directed Research & Development program, which provides resources for Jefferson Lab personnel to make rapid and significant contributions to critical science and technology problems relevant to the mission of Jefferson Lab and the DOE.
A Multidisciplinary Approach
The project was conceived and launched by Rongli Geng in October 2021 before he transitioned to Oak Ridge National Laboratory. It has now shifted to a larger and more multi-disciplinary team led by Weisenberger and Dhakal, the current co-principal investigators.
Weisenberger’s team researches detector technology for nuclear physics research, whereas Dhakal’s work focuses on developing SRF cavities to accelerate electrons at high speeds. Weisenberger says that the multidisciplinary approach will bring together their expertise as they branch out together into the less familiar territory of this LDRD project.
Both principal investigators remark that the project is moving forward well, thanks to the diligence and expertise supplied by every member of the team. Team members include John Musson, Frank Marhauser, Haipeng Wang, Wenze Xi, Brian Kross and Jack McKisson.
“It’s an interesting step outside of the usual things that we do,” Weisenberger said. “The LDRD program lets loose Jefferson Lab scientists and engineers on a research question that isn’t directly related to what we’re actually hired to do, but is making use of all the expertise that we bring and it’s a great resource to tap to try to stretch. That’s what we’re doing with this project, stretching.”
Building and Testing
Before turning the project over the Weisenberger and Dhakal, Geng and his colleagues had determined the required parameters of the cavity and electric field with simulations and calculations.
“We have everything on paper but we have to make it into a reality,” Dhakal said.
The team is currently setting up the experiment in real life.
“We have to see if what was simulated can actually happen,” Weisenberger said.
First, they’ll assemble a mock-up of the experiment at room temperature. Then, they’ll circulate liquid helium around the outer surfaces of the cavity to cool it to superconducting temperatures approaching absolute zero.
Next comes the most difficult part. They must get a single microscopic particle in the correct region of the cavity while the cavity is locked up inside a containment vessel at superconducting temperatures, under vacuum, and with the electric field on.
“We’ve come up with a way to remotely launch a particle in the cavity under experimental conditions, we just have to test it now,” Weisenberger said. “In the research and development world, you often can’t do what you thought you could do. We try and test and run into problems, try to solve the problems, and keep going.”
This is a year-long project with the possibility of another year of funding, depending on how things go. It is also an early stage, proof of principle project. If it is ultimately successful, there would still be a long road of R&D before the concepts could be applied toward building quantum computers. Such computers would require levitating and imparting quantum states on tens to hundreds to thousands of much smaller particles predictably and reliably.
Still, the researchers are looking forward to the discoveries they hope this study will enable regarding microscopic particle levitation and potential observation of a quantum state.
“I’m optimistic,” Dhakal said. “Either way, we’ll discover something. Failure is just as much a part of R&D as success. You learn from both. Basically, whether the particle levitates or not, or whether we can impart the quantum state to it or not, it’s something that’s never been done before. It’s very challenging and exciting.”
The team already has a research paper in the works for this project, but only time will tell whether they can realize this bit of magic in the laboratory.


Quantum computers are predicted to be faster than any supercomputer that can be built with silicon chips.
The laws of physics are supposed to be symmetrical in time and space. That means a ball thrown at a certain speed and in a certain direction would always go the same distance, no matter when you throw or where on Earth you throw it (assuming no other factors, like weather, came into play).
There are, however, things that do break space symmetry. Magnets have north and south poles, which means the magnetic spins of atoms within a magnet are not, as would be expected, spread in all directions but aligned in one direction or another. The same is true of crystals. Though fixed in space, some atoms in a crystal have preferred positions, which makes them appear different based on where you observe them from.
Time symmetry, however, never breaks. The Nobel Prize-winning physicist Frank Wilczek noticed this and started asking questions.
What if, for example, you threw the ball once at 12pm on Friday, and then again at 10am on Tuesday, at the exact same speed in the exact same conditions—and the two throws went a completely different distance? Wilczek knows that, in the macro world, that wouldn’t happen. But as Albert Einstein once pointed out, things get “spooky ” at the atomic level. In 2012, Wilczek proposed that perhaps at the atomic level it would be possible to create a type of matter that broke time symmetry; he called it a “time crystal.”
The idea kicked off a storm of interest. Soon, however, calculations by Masaki Oshikawa at the University of Tokyo showed that time crystals would be impossible. His team found any system in the lowest energy state and in equilibrium would not be able to break time symmetry.
By equilibrium, physicists mean all molecules of, say, water in the liquid state have at least a certain amount of energy. If you add energy in the form of heat to liquid water, all the molecules that gain a certain amount of energy will reach a new equilibrium, becoming steam and enter a new state of matter. Every distinct state of matter we know about is in equilibrium.
However, if physicists could get matter to enter a nonequilibrium state, they could also, based on Oshikawa’s calculations, make time crystals. If they do, it would be a hitherto unknown state of matter. The trouble was physicists didn’t know how to do it—until now. Two studies published in Nature March 9 show such nonequilibrium states can be entered and matter in those states can be classified as types of time crystals.
Christopher Monroe, a physicist at the University of Maryland-College Park, created the system using 10 charged atoms of the element ytterbium and four sets of lasers. One laser converted each ytterbium atoms into a magnet. Another laser naughtily caused disorder to ensure the atoms were in a nonequilibrium state. Then, a third laser made the magnetic atoms to flip—as if the north pole switched to the south pole in a large magnet.
The combination of these three lasers (the fourth was used to read the status of each atom) caused the atoms to oscillate, but at twice the frequency at which their magnetic states were being flipped. In other words, it broke time symmetry.
“It’s like playing with a jump rope, and somehow our arm goes around twice but the rope only goes around once,” Yao told Nature.
Mikhail Lurkin, a physicist at Harvard University, also created a time crystal but in a different system. He used a “dirty” diamond, which is like a normal diamond but has lots of nitrogen atom impurities. He used microwave pulses to flip the spins of nitrogen atoms—and, it turned out, just like Monroe’s ytterbium atoms, the frequency at which the atoms flipped their spin different from the frequency of the pulses.
The time crystals created by Monroe and Lurkin are slightly different than the ones Wilczek proposed. They require regular inputs of energy, which Wilczek’s time crystals would not have needed.
“It’s less weird than [Wilczek’s] idea, but it’s still fricking weird,” Yao told Nature.
Because of this difference, not everyone is convinced what the physicists have achieved are actually time crystals.
“This is an intriguing development, but to some extent it’s an abuse of the term,” Oshikawa told Nature.
The creators of the newly announced time crystals aren’t fussed about definitions. They are, instead, excited by the possibility of using their methods to accelerate the development of quantum computers, which are predicted to be faster than any supercomputer that can be built with silicon chips.
Quantum computers require atoms to exist in entangled states, where changing the state of one automatically causes the other to change state too. At present, such states can be achieved only at extremely low temperatures. Lurkin got all the nitrogen atoms in his dirty diamond to change position together at a constant frequency—meaning they were held in quantum entanglement—and he did it at room temperature.
“In my main job, I use atoms to create quantum computers,” Monroe told me. “Our finding could help create larger quantum computers that don’t need to be at such cold temperatures.”


Science education in schools has a long way to go to be taken seriously, and this is why it is so important to get teachers in the classroom to understand how to teach it.
It is not enough to teach that which is taught, but that which cannot be taught.
We need to teach what is really going on, as opposed to what is shown in a lecture.
So, let’s start with the basics of science education.
What is science?
Scientific knowledge is the process of discovering, analyzing and understanding the nature of the world around us.
We are all born with this knowledge.
It’s not something that can be learnt, but we need to be taught to be able to understand it, and it is crucial to do that in a classroom setting.
The first step is to have a good understanding of science.
Science is a collection of things that we observe, think about and understand, and they have a physical basis.
The process of discovery is the understanding of these things.
What this means is that we are constantly making discoveries, trying to understand the world in new ways and then coming up with new explanations for them.
So it is the idea that everything we do has a physical cause.
When we study, for example, the way the Earth rotates, we are actually looking at the behaviour of something that is happening on the surface of the Earth.
The motion of the planet is a mathematical function that is measured, and so is the behaviour.
This is a physical theory.
We know this because we have a telescope that sees through the sky, but it is also possible to look through the atmosphere and see the behaviour as well.
And this is the physics of how things interact.
The second step is the description of the universe as we see it.
We live in a scientific world, where all the elements of our universe are observable.
So there are different types of observational evidence that can provide clues to how the world is, and the universe has a certain kind of physical structure.
It does not change.
So how do we explain the laws of physics, for instance?
We can do this by measuring the motions of objects and their properties, which are then described using equations, and we can then compare these to the behaviour in nature.
There are two kinds of physical theories that can help us understand the universe: quantum mechanics and general relativity.
In quantum mechanics, you are looking at particles, called quarks, that can move in very particular ways.
This means that there are things that can behave in a particular way.
And these quarks are called elementary particles.
They have properties like momentum, mass, spin and charge.
They are called general relativity because we can use the laws that describe the behaviour and interactions of the particles to describe the laws on the ground that they are travelling through.
In general relativity, we use the Einstein equations, which describe how gravity works.
We measure the speed of light, and look at how light behaves, and see if it behaves in a certain way.
These equations are the same as those used by quantum mechanics.
In fact, you could use these equations in physics too, as you might know by now.
There is a third kind of theory, which is called quantum entanglement.
This applies to the way in which certain particles interact with other particles, which then can create quantum states.
This can give us new ideas about the world.
You can think of it like having an entangled toy, where each time you press on the toy it causes it to move.
The result of this interaction is an entangled state.
These are what quantum theory describes, but they are not the same thing as the elementary particles we are looking for.
In the next step, we learn about what the world looks like when we look at the universe.
When you look at an image on the wall, or a photograph on a wall, you can see how that image or photograph looks, and what the colour of the image is.
In this step, you will also learn how the laws governing the universe relate to these different types.
These three steps help you understand the way our universe behaves.
There might be other things that you can study in school, such as astronomy, but there are also other things you need to learn, like geology and mathematics.
The final step is learning to use these concepts to understand what is going on in the world, and to solve problems.
Science education The idea that science is a science that is taught in schools is not new.
Many of the sciences that we know have been taught in classrooms over the past century.
In science education, we should take these lessons from our history of teaching science to our present day.
Science in schools was always a science subject in the schools.
There was no such thing as a scientific society, no national curriculum or national standards of knowledge.
So when science education was introduced, there were no national standards.
But, as we learn from our own history, there is an important lesson in this.
Science was always taught in a way that it was not


What are quantum computers?
Quantum computers work in a different way to conventional computers. While the latter are binary and store information in the form of 0 or 1, quantum computers use a system of measurement based on quantum physics and the nature of matter itself, called qubits. These are subatomic particles that can be zero, one or a linear combination of both. That combination is called superposition. It means they can store and simultaneously process far more data in far less physical memory space than binary machines. For example, 8 bits on binary systems will represent any number between 0 and 256, while 8 qubits can represent all those numbers at the same time.
That explanation is a gross over-simplification for a technology that’s innately hard to understand. What it means is that quantum computers should handle bigger problems and vastly larger data sets than conventional PCs, enabling analysis of vast amounts of data that couldn’t be solved – or even stored – until now, and all at the same time.
That last element is key. “As opposed to a classical computer that must, essentially, trial every route before deciding on the optimum, quantum computers have the potential to provide an optimum by taking all routes into account at the same time,” explained researchers from GlobalData. In 2019, Google demonstrated how a quantum computer could solve in minutes a problem it would take conventional computers 10,000 years to solve.
This is still a relatively early-stage technology, and while Google, IBM, Microsoft, PsiQuantum, governments and startups are developing quantum computing technologies, they are expensive, suffer from decoherence, require error correction, and don’t yet scale beyond a certain point, typically 50 or 60 qubits. This is subject to change: IBM promises its 127-qubit Quantum Eagle processor in 2021 and says it will introduce 1,000+ qubit systems by 2023. The technology will eventually become sufficiently mature to meet real-world challenges.
What will this mean for business?
As the technology improves, it will be applied. Boston Consulting Group (BCG) recently predicted quantum computing will add up to $850 billion in economic value by 2050.
“Recent advances and roadmaps from major hardware companies such as IBM, Google, Honeywell, IonQ, PsiQuantum and others have increased the confidence that we will have machines powerful enough to tackle important business and society problems before the end of this decade. Impacted companies and governments should get prepared for an accelerated timeline,” said BCG partner, Jean-Francois Bobier.
But how will the technology create this value?
Bobier believes use of quantum computers to run vast simulations will benefit medical research and drug discovery, battery design and fluid dynamics. “For a top pharma company with an R&D budget in the $10 billion range, quantum computing could represent an efficiency increase of up to 30%,” BCG states. Sci-tech research can also reach new frontiers: Google researchers used quantum computing to demonstrate a genuine “time crystal,” a piece of matter that evades the second law of thermodynamics.
These systems may enable government and enterprise to optimize logistics and insurers to better manage risk, while machine-learning advances may help protect against (and, perhaps, enable) online crime and fraud and become the mind in autonomous vehicle systems. Military uses may include radar, highly-secure, very-long-distance communications and submarine detection systems as are being developed in China.
Many financial institutions, including JP Morgan, Goldman Sachs and Wells Fargo are exploring how the tech can be applied to financial instruments such as stocks. An April 2021 Goldman Sachs report showed risk analysis could be conducted at 1,000 times the speed of existing technologies but warned of high error rates at this time. Quantum computer hardware capable of running such tests successfully are expected to become available in 10-20-years’ time.
Most quantum computing reports always note the security use cases cryptography and encryption. Quantum computers are expected to be capable of breaking existing encryption but, conversely, should also enable the development of more powerful encryption standards. In Europe, the European quantum communication network EuroQCI is developing an ultra-secure EU-wide communications infrastructure to secure critical infrastructure. In France, President Emmanuel Macron announced a 1.8 billion Euro Quantum Plan initiative for supporting research and development of quantum technologies. France isn’t alone. China, the U.S., UK, and many other nations are investing billions in what is becoming a quantum computing arms race for technological supremacy.
Quantum computers may also contribute to the struggle against climate change, according to a BCG report. Because they can model complex molecular interactions existing computers cannot, they may enable researchers to innovate technological solutions that reduce emissions in carbon-intensive industries like construction, fertilizer production and transportation. “Quantum computing could help bring more low-carbon technologies into economic reach,” says BCG. “It is in the best interest of governments and companies to fast-track progress in the race for our future.”
Oxford Quantum Circuits launched the UK’s first quantum computing as a service (QaaS) platform in July. Clients can access these machines via the cloud to identify the impact on their business. “Early adopters will have the advantage of understanding what [quantum] means in terms of their market and their business,” said Dr. Ilana Wisby. IBM and other big names also support online access to quantum computing resources.
QaaS platforms may play an important part in making the benefits of this machinery available. A commercial 50 qubit quantum computer costs in the region of $15 million, not to mention running and maintenance costs. The cost and fragility of quantum systems will limit their appeal for some time yet.
Orange is involved with three European projects investigating quantum communications: CiViQ (Continuous Variable Quantum Communications), OPENQKD (Open European Quantum Key distribution testbed) and the QOSAC (Quantum Overarching System Architecture Concepts). Also read about quantum cryptography and quantum teleportation and the race to build the quantum Internet.
Jon Evans is a highly experienced technology journalist and editor. He has been writing for a living since 1994. These days you might read his daily regular Computerworld AppleHolic and opinion columns. Jon is also technology editor for men's interest magazine, Calibre Quarterly, and news editor for MacFormat magazine, which is the biggest UK Mac title. He's really interested in the impact of technology on the creative spark at the heart of the human experience. In 2010 he won an American Society of Business Publication Editors (Azbee) Award for his work at Computerworld.


Quantum researchers have managed to simulate the reversal of time at the quantum scale, using IBM’s quantum computers. Although the effect is simulated, the implication of this experiment is that the arrow of time doesn’t necessarily have to flow in one direction, but can be reversed, allowing what once was to be once again.
The passage of time, at least here in the macroscopic world that we live in, travels in only one direction (that’s forward for those of us that perceive otherwise), and that effect is marked by the concept of entropy, in which isolated systems continually fall into an increasing state of disorder, like the erosion of a mountain into smaller rocks and sand, or the scattering of a set of racked billiard balls after the break. Interestingly, entropy is virtually the only quantity in the physical sciences that requires the arrow of time to move in one direction; otherwise, the application of most physical laws can work just as well backwards as they do forward. An extremely simple mathematical example would be that 1+2=3, but the equation also works in reverse: 2+1=3.
Quantum physicists from the Moscow Institute of Physics and Technology, along with colleagues in Switzerland and the U.S, decided to see if they could reverse the state of disorder in an isolated system, for instance in a single electron, effectively hitting the rewind button on entropy.
“Suppose the electron is localized when we begin observing it. This means that we’re pretty sure about its position in space,” explains study co-author Andrey Lebedev from MIPT and ETH Zurich. “The laws of quantum mechanics prevent us from knowing [its position] with absolute precision, but we can outline a small region where the electron is localized.” But with the passage of time, the boundaries of the electron become smeared over an increasingly larger area of space, indicating an increasing state of chaos associated with the particle—this is the concept of entropy at work.
Basically, over the course of the observation of the electron, the particle falls into an ever increasing state of chaos. While we don’t see the opposite happen in our everyday world, the laws of quantum mechanics don’t actually prohibit the electron from falling into a more ordered state. It would be much like billiard balls that are scattered across a table somehow falling into their racked position if the table were jarred in just the right way—an utterly implausible scenario, but certainly not an impossible one.
Armed with that improbability, the quantum scientists turned to a system that could give their proverbial pool table a jolt that had a reasonable chance to actually re-rack the balls: a quantum computer. In this case, the computer’s individual qbits (analogous to the computational “bits” used by a regular computer) would represent individual electrons: each qubit would be allowed to fall out of the well-ordered state that they would start in, and then be given a mathematical “kick” to see if they reverted back to their earlier ordered state from the resulting chaotic one.
The experiment was conducted in four stages: the first stage was to set the individual qubits to their initial “ground” state—racking the billiard balls, as it were—a highly ordered configuration that would be analogous to the localization of an electron in a small region.
In stage two, the break shot is made. The researchers allowed the ordered state of the qubits to degrade into chaos, much like how the position of our imaginary electron would appear to become smeared over an increasingly large area of space as the passage of time increases. Needless to say, this was the simplest stage, since natural entropy did all the work.
Stage three: back to the past! Once the state of the qbits had reached a sufficient state of disorder, a special program was then run that modified the state of the computer—the improbable “kick” given to the billiard table to send the balls back to their racked position—to simulate an effect on our isolated electron that would otherwise appear to be a chaotic happenstance, such as a random fluctuation in the cosmic microwave background (CMB), the faint background radiation left over from the birth of the Universe.
In stage four, the disordered state of the qbits would revert to their initial state, simulating the reversal of time in our hypothetical electron to an earlier, more ordered state. Or, returning to our billiard table analogy, the improbable circumstance of a movement in the table causing the balls to return to their racked position.
Each iteration of the experiment had a high success rate, with 85% of the cases returning to their ground state when two qubits were used. However, when three qbits were used, the experiment only had a 50/50 chance of succeeding, apparently due to errors caused by imperfections present in the computers themselves.
But what does this mean in terms of real-world applications? “Our findings break ground for investigations of the time reversal and the backward time flow in real quantum systems,” according to the study paper. The research team predicts that this experiment could also help improve future quantum computing systems. “Our algorithm could be updated and used to test programs written for quantum computers and eliminate noise and errors,” according to Lebedev.
- “Great Andromeda Nebula by Isaac Roberts, 1899.” Andromeda galaxy (M31) is two million light-years away. Thus we are viewing M31’s light from two million years ago, a time before humans existed on Earth. via Wikimedia Commons
News Source: phys.org
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Quantum computers are a new type of machine that operate on quantum mechanical hardware and are predicted to give enormous speed advantages in solving certain problems.
Research groups at leading universities and companies, including Google, Microsoft and IBM, are part of a worldwide race to realise the first quantum computer that crosses into the 'quantum computational singularity'. This represents a problem so complex that today's top supercomputer would take centuries to find a solution, while a quantum computer could crack it in minutes.
Now a team of scientists from Bristol have discovered that the boundary to this singularity is further away than previously thought. The research is reported inNature Physics.
The results apply to a highly influential quantum algorithm known as 'boson sampling', which was devised as a very direct route to demonstrate quantum computing's supremacy over classical machines.
The boson sampling problem is designed to be solved by photons - particles of light - controlled in optical chips - technology pioneered by Bristol's Quantum Engineering and Technology Labs (QETLabs).
Predicting the pattern of many photons emerging from a large optical chip is related to an extremely hard random matrix calculation.
With the rapid progress in quantum technologies, it appeared as though a boson sampling experiment that crossed into the quantum computational singularity was within reach. However, the Bristol team were able to redesign an old classical algorithm to simulate boson sampling, with dramatic consequences.
Dr. Anthony Laing, who heads a group in QETLabs and led this research, stated: "It's like tuning up an old propeller aeroplane to go faster than an early jet aircraft. We're at a moment in history where it is still possible for classical algorithms to outperform the quantum algorithms that we expect to ultimately be supersonic. But demonstrating such a feat meant assembling a crack team of scientists, mathematicians, and programmers."
Classical algorithms expert Dr. Raphaël Clifford, from Bristol's Department of Computer Science, redesigned several classical algorithms to attack the boson sampling problem, with the 1950's Metropolised Independence Sampling algorithm giving the best performance.
The simulation code was optimised by QETLabs researcher 'EJ', a former LucasArts programmer. Expertise on computational complexity came from Dr. Ashley Montanaro, of Bristol's School of Mathematics, while QETLabs students Chris Sparrow and Patrick Birchall worked out the projected performance of the competing quantum photonics technology.
At the heart of the project and bringing all these strands together was QETLabs PhD student and first author on the paper, Alex Neville, who tested, implemented, compared, and analysed, all of the algorithms.
He stated: "The largest boson sampling experiment reported so far is for five photons. It was believed that 30 or even 20 photons would be enough to demonstrate quantum computational supremacy."
Yet he was able to simulate boson sampling for 20 photons on his own laptop, and increased the simulation size to 30 photons by using departmental servers. Alex Neville added: "With access to today's most powerful supercomputer, we could simulate boson sampling with 50 photons."
The research builds on Bristol's reputation as a centre of activity for quantum science and the development of quantum technologies.
Through QETLabs, the university has embarked on an ambitious programme to bring quantum technologies out of the laboratory and engineer them in to useful devices that have real-world applications for tackling some of society's toughest problems.
In addition to collaborations with tech companies such as Microsoft, Google, and Nokia, start-ups and new business activities focused on quantum technologies have emerged in Bristol.
An important theme across the overall quantum research activity is developing our understanding of exactly how quantum technologies can provably outperform conventional computers.
Recently Dr. Montanaro, together with Professor Noah Linden of the School of Mathematics, organised a Heilbronn Focused Research Group on the topic of quantum computational supremacy.
This meeting brought some of the world leaders in the field, from both industry and academia, to Bristol for a week of intense discussions and collaboration. Among the attendees was one of the theorists who devised boson sampling, Professor Scott Aaronson, from the University of Texas at Austin.
Although outperforming classical computers might take a little longer than originally hoped, Dr. Laing is still optimistic about the prospects for building a device to do just that. He stated: "We now have a solid idea of the technological challenge we must meet to demonstrate that quantum machines can out-compute their classical counterparts. For boson sampling, the singularity lies just beyond 50 photons. It's a tougher nut to crack than we first thought, but we still fancy our chances."
With Dr. Laing's group focused on practical applications of quantum technologies, the current work puts bounds on the size and sophistication of photonic devices that will be required to tackle industrially relevant problems that are beyond the capabilities of today's classical algorithms.
The paper titled "Classical boson sampling algorithms with superior performance to near-term experiments" is authored by A. Neville, C. Sparrow, R. Clifford, E. Johnston, P. Birchall, A. Montanaro and A. Laing and has appeared inNature Physics.


The one thing everyone knows about quantum mechanics is its legendary weirdness, in which the basic tenets of the world it describes seem alien to the world we live in. Superposition, where things can be in two states simultaneously, a switch both on and off, a cat both dead and alive. Or entanglement, what Einstein called “spooky action-at-distance” in which objects are invisibly linked, even when separated by huge distances.
But weird or not, quantum theory is approaching a century old and has found many applications in daily life. As John von Neumann once said: “You don’t understand quantum mechanics, you just get used to it.” Much of electronics is based on quantum physics, and the application of quantum theory to computing could open up huge possibilities for the complex calculations and data processing we see today.
Imagine a computer processor able to harness super-position, to calculate the result of an arbitrarily large number of permutations of a complex problem simultaneously. Imagine how entanglement could be used to allow systems on different sides of the world to be linked and their efforts combined, despite their physical separation. Quantum computing has immense potential, making light work of some of the most difficult tasks, such as simulating the body’s response to drugs, predicting weather patterns, or analyzing big datasets.
Such processing possibilities are needed. The first transistors could only just be held in the hand, while today they measure just 14 nm–500 times smaller than a red blood cell. This relentless shrinking, predicted by Intel founder Gordon Moore as Moore’s law, has held true for 50 years, but cannot hold indefinitely. Silicon can only be shrunk so far, and if we are to continue benefiting from the performance gains we have become used to, we need a different approach.
Advances in semiconductor fabrication have made it possible to mass-produce quantum-scale semiconductors – electronic circuits that exhibit quantum effects such as super-position and entanglement.
The image, captured at the atomic scale, shows a cross-section through one potential candidate for the building blocks of a quantum computer, a semiconductor nano-ring. Electrons trapped in these rings exhibit the strange properties of quantum mechanics, and semiconductor fabrication processes are poised to integrate these elements required to build a quantum computer. While we may be able to construct a quantum computer using structures like these, there are still major challenges involved.
In a classical computer processor a huge number of transistors interact conditionally and predictably with one another. But quantum behavior is highly fragile; for example, under quantum physics even measuring the state of the system such as checking whether the switch is on or off, actually changes what is being observed. Conducting an orchestra of quantum systems to produce useful output that couldn’t easily by handled by a classical computer is extremely difficult.
But there have been huge investments: the U.K. government announced 270 million pounds (about $417 million) funding for quantum technologies in 2014 for example, and the likes of Google, NASA and Lockheed Martin are also working in the field. It’s difficult to predict the pace of progress, but a useful quantum computer could be ten years away.
The basic element of quantum computing is known as a qubit, the quantum equivalent to the bits used in traditional computers. To date, scientists have harnessed quantum systems to represent qubits in many different ways, ranging from defects in diamonds, to semiconductor nano-structures or tiny superconducting circuits. Each of these has is own advantages and disadvantages, but none yet has met all the requirements for a quantum computer, known as the DiVincenzo Criteria.
The most impressive progress has come from D-Wave Systems, a firm that has managed to pack hundreds of qubits on to a small chip similar in appearance to a traditional processor.
The benefits of harnessing quantum technologies aren’t limited to computing, however. Whether or not quantum computing will extend or augment digital computing, the same quantum effects can be harnessed for other means. The most mature example is quantum communications.
Quantum physics has been proposed as a means to prevent forgery of valuable objects, such as a banknote or diamond, as illustrated in the image below. Here, the unusual negative rules embedded within quantum physics prove useful; perfect copies of unknown states cannot be made and measurements change the systems they are measuring. These two limitations are combined in this quantum anti-counterfeiting scheme, making it impossible to copy the identity of the object they are stored in.
The concept of quantum money is, unfortunately, highly impractical, but the same idea has been successfully extended to communications. The idea is straightforward: the act of measuring quantum super-position states alters what you try to measure, so it’s possible to detect the presence of an eavesdropper making such measurements. With the correct protocol, such as BB84, it is possible to communicate privately, with that privacy guaranteed by fundamental laws of physics.
Quantum communication systems are commercially available today from firms such as Toshiba and ID Quantique. While the implementation is clunky and expensive now it will become more streamlined and miniaturised, just as transistors have miniaturised over the last 60 years.
Improvements to nanoscale fabrication techniques will greatly accelerate the development of quantum-based technologies. And while useful quantum computing still appears to be some way off, it’s future is very exciting indeed.