For the last 100 years, due to its unintuitive nature, quantum physics has captured the imagination of physicists worldwide. Recently, there has been a new push by various companies, such as Google, Microsoft, and IBM, and the developed countries to use these bizarre effects of quantum mechanics for the development of a quantum mechanics based devices, e.g., a quantum computer. In a day-to-day classical computer, the information (e.g., picture of a birthday party) is stored and processed using transistors as “bits” that can have one of the two possible values: “0” (OFF state) or “1” (ON state). The quantum computer takes advantage of entanglement and massive parallelism via the superposition principle to solve problems unmanageable by classical computers. Quantum bits or “qubits” are different: in addition to “0” and “1,” a qubit can also exist in a superposition state. If a classical computer is tasked to figure its way out of a complex maze, it will try every single path sequentially, ruling them all out individually until it finds the right one. In contrast, a quantum computer can go down every branch of the maze at once. Hence a quantum computer reduces computational time by millions of times and at a lower energy cost than a classical computer.
The quantum information in a quantum computer can be materialized in different physical forms and converted from one to another without changing its content. The physical implementation choice is left to the “quantum engineer”: either natural microscopic systems such as atoms, ions, photons, electron, and nuclear spins, or more artificial systems such as superconducting qubits. Superconducting qubits are promising candidates for building a quantum computer; they couple very strongly to microwave fields, but exhibit coherence times to tens of microseconds. This limitation allows only a short time window to perform quantum calculations before the whole system decoheres. This time restriction has motivated researchers to look for hybrid quantum systems that increase the coherence time of superconducting qubits by combining them to other quantum systems better protected against decoherence. Researchers are trying to couple superconducting qubits, via a superconducting resonator, to ions, atoms, or spin ensemble.
Recently, magnons have been considered as a new candidate for coherent quantum information processing. Magnons are the collective excitation of spins in magnetic materials. Their frequency range lies from GHz to THz. In comparison to the paramagnetic spin ensembles, magnons can exchange information with a much faster speed and for more cycles before losing coherency, while keeping the device dimension small. To implement the high spin density magnetic materials into practical quantum devices, on-chip integration and miniaturization on a nanoscale are required. To achieve this goal, the following fundamental physics and technological issues must be addressed first: 1) Does the magnonphoton coupling scales as we systematically reduce the dimensions of the magnetic element into the nanoscale regime? 2) Are their critical dimensions (either in length, width, or height) of magnetic elements where magnon-photon coupling enhances or reduces non-linearly? 3) Can we tune the magnonphoton coupling via placing arrays of nanomagnets? Specifically, do arrays of nanomagnets on particular lattices or particular magnetic materials allow better magnon-photon coupling? 4) What is the effect on magnon-photon interaction as we vary the fundamental dipolar and exchange interactions among the nanobars? 5) Can we artificially tune the magnon-photon coupling by reprogramming magnetic arrays using a 2-D magnetic field protocol?
My goal is to address the above questions using a systematic approach that includes several state-ofthe-art experimental and simulation techniques. We will miniaturize high spin density magnetic thin films using nanofabrication methods. These devices will be incorporated with superconducting microwave resonators to make an on-chip device. We will also construct a novel equipment package that will allow us to study the magnon-photon coupling in arrays of nanomagnets on periodic and quasicrystal lattices as a function of magnetic field, frequency, and temperature. We will utilize a two-dimensional magnetic field protocol to program the magnetic state of nanomagnets to tune the magnon-photon coupling. Furthermore, using the micro-focus Brillouin light scattering technique, we will image the spatial magnon profile. This will give unprecedent mesoscopic understanding of space dependent magnon profile as the magnetic material is miniaturized towards 100 nanometers length scale.
Our member Dr. Vinayak Bhat has recived funding from SONATA BIS 10 (ST panel) financed by NCN. Project title is „Study of the effect of the nanostructured periodic and quasicrystal nanomagnet lattices on magnon-photon coupling”


Cryptocurrency is the digital form of currency that is secured by cryptography. All crypto-related transactions are decentrally controlled.
The digital payment system- cryptocurrency doesn’t rely on banks to validate transactions. Peer-to-peer technology makes it possible for anybody, anywhere, to send and receive payments.
Payments made using cryptocurrencies do not exist as actual physical coins that can be transported and exchanged; rather, they only exist as digital entries to an online database that detail individual transactions. A public ledger keeps track of all bitcoin transactions that involve money transfers. Cryptocurrencies are digital money kept in digital wallets.
Cryptocurrency uses strong coding and encryption to secure end-to-end security for all transactions. strong coding is involved in storing cryptocurrency and all the public ledger to ensure the top safety of all the money.
How does cryptocurrency Strong work?
A distributed public ledger known as the blockchain, updated and maintained by currency holders, is the foundation of cryptocurrencies.
Through a process known as mining, which employs computer power to solve challenging mathematical problems, units of Bitcoin are created. Additionally, users can purchase the currencies from brokers and then store and spend them in digital wallets.
When you hold cryptocurrencies, you don’t own anything. What you possess is a key that enables you to transfer a record or a measurement unit between people without using a reliable third party.
Although the first cryptocurrency- Bitcoin, has been around since 2009, cryptocurrencies and blockchain technologies are still emerging. New people regularly work on these technologies to make them better financial tools.
What is a Bitcoin?
Bitcoin was the first-ever cryptocurrency. It was founded in 2009. It’s the most famous and most commonly used cryptocurrency. Satoshi Nakamoto developed Bitcoin.
Bitcoin is a digital currency and operates freely using cryptography and the public ledger. The public ledger has all the transactions, and the peer-to-peer network has copies of the public ledger. Anyone with a computer can join this general by setting up the server using the nodes. Instead of relying on a single trust point, such as a bank, these nodes cryptographically decide who will own which bitcoin.
Every transaction is shared across nodes and broadcast to the network in a public manner. Miners gather these transactions into a collection called a block, which is added permanently to the blockchain about every 10 minutes; this is the official bitcoin account book.
Virtual currencies are held in digital wallets and can be accessed using client software or a variety of internet and hardware solutions, similar to how you would maintain traditional money in a physical wallet.
What is the purpose of Bitcoin?
Bitcoin was developed as a means of online money transfer. The goal of digital currency was to offer a different form of payment that would function without centralised management but otherwise function similarly to traditional currencies. Every bitcoin transaction is publicly visible and is shared on its node-to-node network. Every transaction is recorded, and the miners add the transactions in a block that further forms the blockchain. At the outset, bitcoin is not a wallet or even currency. It’s a consensual agreement among the network. Bitcoins and cryptocurrencies operate on private keys and passwords and can be transferred easily.
Is Bitcoin safe?
The US National Security Agency’s SHA-256 algorithm serves as the foundation for the cryptography used by bitcoin. Since more potential private keys would need to be checked than there are atoms in the universe, it is practically impossible to crack them.
Although there have been several high-profile instances of bitcoin exchanges being hacked and having money stolen, these firms almost always kept the digital currency for the benefit of their users. In these instances, the websites were hacked and not the Bitcoin network.
The fact that bitcoin has no centralised control is a real issue. Anyone making a mistake with a transaction on the wallet has no redress. There is no one to contact if you unintentionally transmit bitcoins to the incorrect person or forget your password.
Naturally, it might all be destroyed if practical quantum computing ever becomes a reality. Since quantum computers operate differently from conventional computers, they may be able to do many mathematical computations essential to cryptography in a fraction of a second.
What is a polygon?
Polygon is a platform that supports different blockchain projects, founded by Jaynti Kanani, Anurag Arjun, Sandeep Nailwal and Mihaela Bjelic.
With the symbol MATIC, Polygon is both a cryptocurrency and a platform for connecting and expanding blockchain networks. In 2017, Polygon—”Ethereum’s internet of blockchains”—was introduced as Matic Network.
The Polygon platform connects Ethereum-based projects and runs on the Ethereum blockchain. While maintaining the security, interoperability, and structural advantages of the Ethereum blockchain, the Polygon platform can boost a blockchain enterprise’s flexibility, scalability, and sovereignty.
MATIC is secured via an ERC-20 token compatible with Ethereum-based digital currencies. Matic is used to governing the polygon network and ensure it’s secure. Polygon network also brings out the limitations of the Ethereum network and gives us better options to operate on with high reliability and fewer transaction fees.
What is the purpose of a Polygon?
Polygon work on a proof of stake method, which ensures consensus through every block.
Polygon allows you to create custom blockchain networks. It bridges the communication between blockchains and Ethereum. It also aids other blockchain networks to be compatible with Ethereum.
Cryptocurrencies are the future of digital currency. It is here to stay, and it’s growing exponentially. The world of cryptography has entered so many arenas, proving its security and worth. Before investing in any crypto, be it bitcoin, Ethereum, Litecoin, Ripple etc., do your part of the research and then hop onto the trends.
When Bitcoin was founded, it was made to make everyday transactions easier. Although it’s still not widely used, many websites and places accept Bitcoin against the purchase. Websites that accept cryptocurrencies are majorly technology-related sites, cars, insurance, luxury goods, e-commerce etc. But you should also be aware of fraudulent websites as they can be scammers and steal the code for your cryptocurrency.


In the ancient world, they used cubits as an important data unit, but the new data unit of the future is the qubit — the quantum bits that will change the face of computing.
Quantum bits are the basic units of information in quantum computing, a new type of computer in which particles like electrons or photons can be utilized to process information, with both “sides” (polarizations) acting as a positive or negative (i.e. the zeros and ones of traditional computer processing) alternatively or at the same time.
According to experts, quantum computers will be able to create breakthroughs in many of the most complicated data processing problems, leading to the development of new medicines, building molecular structures and doing analysis going far beyond the capabilities of today’s binary computers.
The elements of quantum computing have been around for decades, but it’s only in the past few years that a commercial computer that could be called “quantum” has been built by a company called D-Wave. Announced in January, the D-Wave 2000Q can “solve larger problems than was previously possible, with faster performance, providing a big step toward production applications in optimization, cybersecurity, machine learning and sampling.”
IBM recently announced that it had gone even further — and that it expected that by the end of 2017 it would be able to commercialize quantum computing with a 50-qubit processor prototype, as well as provide online access to 20-qubit processors. IBM’s announcement followed the September Microsoft announcement of a new quantum computing programming language and stable topological qubit technology that can be used to scale up the number of qubits.
Taking advantage of the physical “spin” of quantum elements, a quantum computer will be able to process simultaneously the same data in different ways, enabling it to make projections and analyses much more quickly and efficiently than is now possible.
There are significant physical issues that must be worked out, such as the fact that quantum computers can only operate at cryogenic temperatures (at 250 times colder than deep space) — but Intel, working with Netherlands firm QuTech, is convinced that it is just a matter of time before the full power of quantum computing is unleashed.
“Our quantum research has progressed to the point where our partner QuTech is simulating quantum algorithm workloads, and Intel is fabricating new qubit test chips on a regular basis in our leading-edge manufacturing facilities,” said Dr. Michael Mayberry, corporate vice president and managing director of Intel Labs. “Intel’s expertise in fabrication, control electronics and architecture sets us apart and will serve us well as we venture into new computing paradigms, from neuromorphic to quantum computing.”
The difficulty in achieving a cold enough environment for a quantum computer to operate is the main reason they are still experimental, and can only process a few qubits at a time — but the system is so powerful that even these early quantum computers are shaking up the world of data processing. On the one hand, quantum computers are going to be a boon for cybersecurity, capable of processing algorithms at a speed unapproachable by any other system.
By looking at problems from all directions — simultaneously — a quantum computer could discover anomalies that no other system would notice, and project to thousands of scenarios where an anomaly could turn into a security risk. Like with a top-performing supercomputer programmed to play chess, a quantum-based cybersecurity system could see the “moves” an anomaly could make later on — and quash it on the spot.
The National Security Agency, too, has sounded the alarm on the risks to cybersecurity in the quantum computing age.
“Quantum computing will definitely be applied anywhere where we’re using machine learning, cloud computing, data analysis. In security that [means] intrusion detection, looking for patterns in the data, and more sophisticated forms of parallel computing,” according to Kevin Curran, a cybersecurity researcher at Ulster University and IEEE senior member.
But the computing power that gives cyber-defenders super-tools to detect attacks can be misused, as well. Last year, scientists at MIT and the University of Innsbruck were able to build a quantum computer with just five qubits, conceptually demonstrating the ability of future quantum computers to break the RSA encryption scheme.
That ability to process the zeros and ones at the same time means that no formula based on a mathematical scheme is safe. The MIT/Innsbruck team is not the only one to have developed cybersecurity-breaking schemes, even on these early machines; the problem is significant enough that representatives of NIST, Toshiba, Amazon, Cisco, Microsoft, Intel and some of the top academics in the cybersecurity and mathematics worlds met in Toronto for the yearly Workshop on Quantum-Safe Cryptography last year.
The National Security Agency, too, has sounded the alarm on the risks to cybersecurity in the quantum computing age. The NSA’s “Commercial National Security Algorithm Suite and Quantum Computing FAQ” says that “many experts predict a quantum computer capable of effectively breaking public key cryptography” within “a few decades,” and that the time to come up with solutions is now.
According to many experts, the NSA is far too conservative in its prediction; many experts believe that the timeline is more like a decade to a decade and a half, while others believe that it could happen even sooner.
And given the leaps in progress that are being made on almost a daily process, a commercially viable quantum computer offering cloud services could happen even more quickly; the D-Wave 2000Q is called that because it can process 2,000 qubits. That kind of power in the hands of hackers makes possible all sorts of scams that don’t even exist yet.
For example, forward-looking hackers could begin storing encrypted information now, awaiting the day that fast, cryptography-breaking quantum computing-based algorithms are developed. While there’s a possibility that the data in those encrypted files might be outdated, there is likely to be more than enough data for hackers to use in various identity theft schemes, among other things.
It’s certain that the threats to privacy and information security will only multiply in the coming decades.
In fact, why wait? Hackers are very well-funded today, and it certainly wouldn’t be beyond their financial abilities to buy a quantum computer and begin selling encryption-busting services right now. It’s likely that not all the cryptography-breaking algorithms will work on all data, at least for now — this is a threat-in-formation — but chances are that at least some of them will, meaning that even now, cyber-criminals could utilize the cryptography-breaking capabilities of quantum computers, and perhaps sell those services to hackers via the Dark Web.
That NSA document that predicted “decades” before quantum computers become a reality was written at the beginning of 2016, which shows how much progress has been made in barely a year and a half. The solution lies in the development of quantum-safe cryptography, consisting of information theoretically secure schemes, hash-based cryptography, code-based cryptography and exotic-sounding technologies like lattice-based cryptography, multivariate cryptography (like the “Unbalanced Oil and Vinegar scheme”), and even supersingular elliptic curve isogeny cryptography.
These, and other post-quantum cryptography schemes, will have to involve “algorithms that are resistant to cryptographic attacks from both classical and quantum computers,” according to the NSA. Whatever the case, it’s certain that the threats to privacy and information security will only multiply in the coming decades, and that data encryption will proceed in lockstep with new technological advances.


As electronic devices using conventional materials reach their limits, research focus has shifted to the development of exotic materials with properties that can make electronic devices more efficient, lightweight, flexible, cost-effective and smart. Take a look at some promising candidates.
Most of us assume that smartphones and laptops will keep getting faster and better. But that progress could come to an end in about a decade. That’s when engineers will hit the limits of cramming atom-scale circuitry onto conventional silicon chips, the brains behind every computing device today.
Fortunately, chip market leaders have plenty of ideas to get around that impasse. Their plans begin with refinements to today’s technology and grow steadily more exotic.
Companies are investing big in exotic forms of carbon as a way to recraft chips. Graphene, for example, is a sheet of carbon atoms just a single atomic layer thick, arranged in a hexagonal array that looks like a chickenwire fencing. Another is carbon nanotubes, which are like tiny straws made from rolled up graphene sheets.
Both forms of carbon could help push miniaturisation further than what’s possible with conventional silicon. And processors could get faster even if they don’t get smaller—a big selling point. Nanotubes could become transistor building blocks, although placing them precisely is a big challenge. Researchers also envision tiny transistors made using graphene, but graphene-based chips will pose challenges. The material conducts electrical current well but doesn’t mirror silicon’s semiconductor properties.
One way to keep pushing progress will involve elements drawn from other columns to either side of the group IV column—thus the term III-V materials, pronounced simply ‘three-five.’ With III-V materials, chip manufacturing stays the same but silicon will get new elements layered on top. That will help electrons flow faster, which means less voltage will be needed to get them moving. If the chips need less power, transistors can be smaller and switch faster.
Researchers are creating and investigating artificial and unconventional materials with unusual electronic and magnetic properties like superconductors that transport electricity with zero losses, and very thin materials (just two or three atoms thick) that could be incorporated into transistors.
The novelty of such materials makes it nearly impossible to anticipate everything that they can do. A researcher can make educated guesses about various properties, but end up seeing something entirely different. A deeper understanding of the material opens the possibility that engineers would be able to route electric currents in quantum computers much like the way they do in conventional electronics through silicon. However, creating high-quality topological insulator materials is a challenge. Since the useful properties occur on the surface, nanoscale ribbons and plates would be ideal to work with because of their large surface area.
British researchers won the 2016 Nobel Prize in Physics for their theoretical explanations of strange states (topological phases) of matter in two-dimensional materials. Their work laid the foundation for predicting and explaining bizarre behaviours that experimentalists discovered at the surfaces of materials, and inside extremely thin layers. These include superconductivity—the ability to conduct electricity without resistance—and magnetism in very thin materials.
Physicists are now exploring similar states of matter for potential use in a new generation of electronics including quantum computers. And the theories pioneered by the Nobel winners have been extended to develop exciting materials such as topological insulators.
Topological insulators are a class of solids that conduct electricity like a metal across their surface but at the same time block the current’s flow like a rubber through their interior. Theoretical physicists predicted their existence in 2006 and experimentalists demonstrated the first such material in 2008.
Engineers find a few traits of topological insulators especially exciting. One is that the electrons move in a direction determined by their spin—a quantum-mechanical property that forms the basis of magnetic data storage. Engineers hope to exploit the spin-motion connection to make superfast hard drives.
Topological insulators open the door to tailoring topological electronic properties by stacking different thin sheets, or 2D materials. These exotic 2D materials could be used as a platform for energy-efficient computing (spintronics) and to solve today’s intractable challenges with quantum computing.
Candidate materials for topological insulators
Like graphene, the semi-metal tungsten ditelluride (WTe2) can be prepared in a single monolayer. Tellurium atoms sandwich the transition metal tungsten in each layer. These sandwiched transition metal materials are important for future electronics and photonics. Scientists have predicted that WTe2 in monolayer form has the exotic electronic properties of topological insulators. However, the surface of WTe2 oxidises in air, destroying the electronic properties.
Now, researchers have made devices from WTe2 down to a single layer thick, which are air-stable and have good electrical contacts. Surprisingly, they found that in the case of a single layer, the sheet became insulating at liquid nitrogen temperatures when no gate voltage was applied. For large-enough positive or negative contact voltages, the electrical current switched on, as in a transistor.
This content was originally published here.


Quantum computing has become a buzzword in the IT industry. Some people think it’ll change how we do computing forever and give us more processing power than we ever imagined. Some fear this new technology might break all current encryption and security. Others are creating sci-fi shows based on quantum computing, like Devs, which appears in this list of our community’s favorite TV shows.
But most people, even many developers, aren’t quite sure what quantum computing is. Let’s clear up some of the confusion.
Quantum computing terms you need to know
Before we get into how quantum computing works, let’s look at some key terms that you’ll need to know to understand the concept.
The quantum in quantum computing refers to quantum mechanics. A quantum in physics is the minimum amount of any physical property that can exist.
For instance, a photon is a single quantum of light. Quantization of energy and how it affects the interactions between matter and energy is part of the fundamental framework for describing the physical world.
Qubit is short for quantum bit — the quantum version of the bit we use in classical computing. Standard bits can only be one of two values: 1 or 0. Qubits, on the other hand, hold a superposition of all possible states.
Every quantum state can be represented as a sum of two or more other distinct states, and quantum particles combine all possible states. They remain in all of these states at once until they’re actually observed and measured.
Think of a coin flip. Once the coin lands on the ground, it’ll be heads or tails, but while it’s in the air, it still has a chance of being either one. Quantum computers use the concept of superposition to manipulate qubits and affect their probabilities before making a final measurement to get the answer.
Entanglement is a process by which quantum particles can link up so that their states stay linked no matter how far apart they are in space. They share a unified quantum state and can exert an influence on each other.
By entangling qubits in a quantum computer, more information can be represented simultaneously, giving the quantum computer more computing power and the ability to solve more complicated problems.
In a quantum computer, entanglement is a good thing, but interference is bad. Quantum interference is part of a qubit’s natural behavior that can influence the probability of the final measurement of its superposition. Quantum computers try to reduce interference as much as possible to ensure more accurate results.
How does quantum computing work?
A quantum computer has three main parts.
The first part is the structure that holds the qubits used for computation. These qubits must be stored in a way that minimizes quantum interference. In some quantum computers, superfluids chill the qubit housing to a hundredth of a degree Celsius above absolute zero to keep the qubits stable. Other quantum computers use a vacuum to help with qubit cohesion and minimize interference between them.
The second part is a mechanism for transferring information to the qubits. To use them for computations, their behavior must be controlled so they can hold, change, and read information. There are a few ways to do this. Lasers, microwaves, and voltage are the most common.
The third and final major part of a quantum computer is a standard computer where the code written for the quantum computer is run. It interfaces with the control mechanism, which sends instructions to the qubits.
Where can quantum computing be used?
Quantum computing is still in its early stages, and it’s not quite ready to be used in everyday businesses. Still, some companies are starting to find new uses for the technology.
Most of the work in quantum computing is currently being done by scientists and quantum computing experts who create proof-of-concept applications and test them on a small scale to help identify future uses for the technology. That way, they’ll be ready when quantum hardware develops to the point that it’s practical for more uses.
Also, while a quantum computer can do certain things many magnitudes faster than a classical computer, they don’t do everything quicker and aren’t practical for some computational problems. Here are some of the many industries where quantum computing will have the biggest impact.
The power of quantum computers threatens to make current cryptography techniques obsolete, such as RSA encryption, which is used to secure much of the sensitive data in the digital world. The good news is that there are already companies working on new cryptography techniques that even quantum computers can’t crack.
Machine learning is changing many things about our world, but running machine learning algorithms on traditional computers takes a lot of time and resources. Scientists and Quantum Computing Researchers are looking into new ways to make machine learning faster and more efficient using quantum computers.
Quantum computers have many uses in the healthcare industry. They simulate chemical reactions much faster than standard computers, and they’re also used for protein folding, where they help speed up the creation of new drugs.
Quantum computing is also used in fintech, where its power makes parsing massive amounts of financial data quicker and model creation more accurate. It can also be used in fraud detection and portfolio risk optimization.
Quantum computers are good at optimization. There are many challenges involved in supply chains and international shipping routes that can take a standard computer literally years to solve, but a quantum computer can solve in only minutes.
Programming languages and SDKs used in quantum computing
The programming languages used in quantum computing may have a similar syntax to those used in standard programming, but they were created specifically to handle the quantum computing environment.
But that doesn’t mean you can’t still use standard programming languages. There are high-level SDKs (Software Development Kits) written in languages like Python that allow you to branch into quantum computing without needing to learn a new language.
Here are some of the many programming languages and SDKs used in quantum computing:
- QCL: QCL (Quantum Computing Language) is one of the first programming languages used for quantum computing. Its syntax resembles the C programming language, and its data types are similar to the primitive data types in C.
- Q: Q was the second programming language implemented in quantum computers. It was designed as an extension of C++, so C++ developers can start working with it quickly.
- OpenQASM: OpenQASM (Open Quantum Assembly Language) is a low-level language released by IBM for use with quantum computers.
- Q#: Q# is an open-source quantum programming language offered by Microsoft. It has some features that developers who know the Python, C#, and F# programming languages will recognize.
- Silq: Silq is an open-source high-level programming language written in the D programming language. It’s available on Github and is relatively new. The first version was published in 2020.
- Cirq: Cirq is a Python library created by Google for writing, manipulating, and optimizing quantum circuits. Cirq abstracts away many of the low-level details of quantum hardware in a language familiar to many developers.
- Qiskit SDK: Qiskit is a software development kit created specifically for working with the OpenQASM programming language and IBM Q quantum processors. It’s written in Python, so developers don’t have to have high-level knowledge of quantum hardware to use it.
- Braket SDK: The Braket SDK is yet another quantum computing SDK written in Python that works with Amazon’s proprietary Braket quantum computing platform.
How to get started in quantum computing
As we said, quantum computing isn’t yet practical enough to be used in the average business. So you can’t get a job writing code for quantum computers yet, unless the job is with a business currently experimenting with the technology or building their own quantum computers.
Still, you can experiment with quantum computer coding right now. Here are four places you can do that:
- Amazon Braket: Amazon will give you one free hour per month to experiment with their quantum computing platform, and it provides an SDK written in Python to interact with the Braket platform so you can write quantum code in a familiar programming language.
- IBM Quantum: You can also sign up for an account with IBM to run experiments on their quantum computing platform. You can write your code in Python here using the Qiskit SDK.
- Azure Quantum: You can experiment with the quantum computers that Microsoft has access to, and when you sign up, you can get a free $200 credit.
- DWave Leap: DWave also provides developers with limited free access to their quantum computing platform.
Python is a good choice if you’re ready to jump into quantum computing today since Circ, the Qiskit SDK, and the SDK for Amazon’s Braket are based on the language. Check out our Learn Python 3 course to learn what you need to know to get started. Or, if you’d rather work with some of the low-level languages used for quantum computing, try Learn C++.


The astrolabe, magnetic compass, and telescope were the five significant advances of the Age of Exploration. compass with magnets A compass is a tool for navigation and geographic orientation that displays the cardinal directions. It usually consists of a magnetized needle or other device that may rotate to align itself with magnetic north, such as a compass card or compass rose. Compass – Wikipedia, caravel, sextant, and Mercator’s projection https://en.wikipedia.org wiki CompassCompass – Wikipedia, caravel, sextant, and Mercator’s projection
Similarly, What technology helped the Europeans?
Steel steamships (along with other technology) aided European empires in expanding inland in Africa and Asia, and the discovery of quinine made exploration of the former continent much simpler.
Also, it is asked, What were the 3 technologies that made European exploration easier?
Answers include: mapmakers improved their processes and generated more accurate maps; the astrolabe aided navigation; and the three-masted caravel enabled ships to go farther.
Secondly, How did technology play a role in European exploration?
European expeditions and discovery were also aided by new technologies. Ocean currents and latitude lines were better shown on better maps. Navigation was enhanced by inventions such as the astrolabe and magnetic compass.
Also, What navigation technology was used by explorers?
Astrolabe. Many European explorers, including Columbus and Magellan, employed the astrolabe as one of their most essential navigational aids.
People also ask, What technology did the European settlers bring to America?
Several technical breakthroughs, including as compasses, caravels, and astrolabes, greatly aided European colonization of the Americas. It influenced economic growth by allowing the creation of large-scale trading networks between the Old and New Worlds.
Related Questions and Answers
Why did Europe have better technology?
It may be related to culture, but it is more typically due to other variables like location, environment, available resources, or even population size. Many technical achievements are the result of a lengthy trial and error process involving a great deal of luck and chance.
What were new technologies 1450 1750?
Early Modern Period (1450-1750) Invented in China during the Han Dynasty, the sternpost rudder improves steering. Sails made of lateen may sail in any direction, independent of the wind. Latitude is the measurement of the distance between the sun and the stars above the horizon, as measured by an astrolabe. Chinese magnetic compass – orientation without sight of land
What technologies led to the Age of Exploration and where did they originate?
The Age of Exploration took place during the 1400s and 1500s, during the Renaissance, and it ushered in a spirit of exploration and creativity throughout Europe. The compass, the astrolabe, and innovative ships like the caravel were some of the advancements that made the Age of Exploration feasible.
What helped European exploration success?
A Faster Eastbound Route However, commerce was the most significant motivator for exploration. The historic expedition of Marco Polo to Cathay signified Europe’s “discovery” of Chinese and Islamic cultures. Traders were drawn to the Orient, and exotic goods and money flooded into Europe.
Which technological advancements made it possible for European sailors to reach the Far East?
More precise maps, better ships, and better navigation instruments like the compass or the astrolabe were three technical breakthroughs that helped make European voyages of discovery feasible. The astrolabe was used to calculate the locations of the stars. This allowed sailors to calculate out how much leeway they had when at sea.
How did the astrolabe help European explorers?
The astrolabe, a portable gadget used by sailors to assist them find their way, was one of them. The astrolabe assisted in determining latitude, which is an essential aid in navigation, by measuring the distance between the sun and stars above the horizon.
Which technological improvements led to the era of European exploration?
The astrolabe, magnetic compass, caravel, sextant, and Mercator’s projection were the five significant breakthroughs of the Age of Exploration.
What technology did the First Nations use?
Traditionally, First Nations societies made tools out of natural materials for hunting, fishing, and textile production. Stone, bone, antlers, teeth, and wood were used to make arrow and spearheads by the Dakelh. Caribou skin and plant bark were weaved together to create beaver nets.
What was the role of improved technology in European exploration in the 15th and 16th centuries?
What impact did advancements in technology play in European exploration throughout the 15th and 16th centuries? Ships were able to go quicker because to the steam engine. At sea, the mariner’s astrolabe calculated latitude. The ships were pushed farther by African slave rowers.
Is Europe technologically advanced?
As is customary, East Asian and European nations dominated the top slots in the rankings. Ten of the top 20 nations were in Europe, and five were in East Asia, indicating that the competition for technical growth has a major regional component.
How advanced is Europe in terms of technology?
Europe is currently slipping behind not just the United States and Japan, but even China in terms of technical innovation. China has surpassed the EU in terms of R&D spending, accounting for 2.1 percent of GDP. There isn’t a single European company among the world’s top 15 digital enterprises today.
How did Europe advance faster?
It seems to imply that the industrial revolution in Western Europe was triggered by increased productivity and intense expansion via the use of machines. This makes sense, and it’s likely one of the reasons why Western Europe “advanced” more quickly in the previous several centuries.
What were some examples of technology that developed during the time period of 1450 1750?
Following interactions with Chinese traders, gunpowder, papermaking, block printing, and the compass were all introduced to European civilization.
What technological innovations helped the Europeans to create their maritime empires and how?
What technologies aided Europeans in establishing their maritime empires? New ships and other marine technologies such as lateen sails, updated charts, and an astrolabe are all being developed.
What made European Exploration possible?
God, money, and glory are the three main motivations for European exploration and colonization of the New World, according to historians.
How did the sextant help European explorers?
Navigators and surveyors used sextants to measure the angle between two objects. They were used at sea to calculate the angle between a celestial object and the horizon, such as the sun, moon, planets, and stars.
What were the three main tools of navigation that led to the Age of Exploration?
Lateen sails, the astrolabe, and the magnetic compass are three instruments that are particularly important during this era.
What 4 tools and inventions for navigation improved during the Renaissance?
Navigation required the use of tools such as an hourglass, a quadrant, a compass, and a nautical chart.
What is traditional and Indigenous technology?
Modern technology makes use of natural resources, but indigenous technology makes use of other materials. For example, instead of utilizing industry coal and lime for housing building, you may use charcoal and seashell mortar. Cite.
What did First Nations invent?
Inventions are a fun fact. Other First Nations innovations include canoes and kayaks, darts, lacrosse (a precursor to hockey), petroleum jelly, and cough syrup.
Who has the best technology in the world?
According to a UN survey, Finland is the world’s most technologically sophisticated nation. According to a recent assessment published by the United Nations development program, Finland is the world’s most technologically advanced nation, ahead of the United States (UNDP).
Is Europe behind in tech?
However, Europe is now lagging behind in critical technical infrastructure such as semiconductors and ultrafast telecommunications networks. Cisco in the United States and Huawei in China have constructed the infrastructure that powers the internet for Europe’s 700 million people.
What is the most advanced technology?
9 New Technology Trends to Watch in 2022 Machine Learning and Artificial Intelligence (AI). Automation of Robotic Processes (RPA) Edge Computing is a term that refers to the use of Quantum computing is a term that refers to the use of quantum The terms “virtual reality” and “augmented reality” are used interchangeably.
This Video Should Help:
The “in what two ways did technological innovations lead to the age of exploration” is a question that has many answers. The main answer is that Europeans used technology in order to explore new lands and find new resources.
- what role did mercantilism play in european countries desire to explore
- navigation technology in the 1500s and the age of exploration
- what were some immediate and some long-term outcomes of columbus’ voyage
- technology exploration
- how technology enabled european explorers to navigate to the new world.


Over the past several millennia, humanity has transformed itself from a species of hunter-gatherers into a global and interconnected civilisation. Researchers have long debated the traits of our ancestors which could have allowed such a dramatic metamorphosis to take place, but perhaps the most widely agreed-upon theory has been our ability to convey complex ideas to each other through speech and writing – the rich communication tool which we call human language. As we exchange knowledge with each other in this way, our embodied perception adopts a constant state of change.
Dr Sánchez-Flores proposes that this process is rooted in a phenomenon known as ‘autopoiesis’ – first coined by Chilean biologists Humberto Maturana and Francisco Varela in 1972 to describe the self-maintaining chemistry of living cell populations. For humans, this means that we are continually shaped by what we perceive through our nervous systems, while at the same time, we continually shape our surrounding environments through our embodied exchanges. We express those exchanges to one another using language.
“Human language is a by-product of the relationships that human beings build with one another and on which they depend as organisms to survive, thrive, and emerge as persons”, Dr Sánchez-Flores explains. “Human beings as living organisms engage in autopoiesis and the languages we produce are both enabled by our human biology and enable our own autopoiesis.” Yet on a deeper level, researchers in the past haven’t widely examined how the autopoietic nature of our use of language is connected with wider concepts that can help us understand how life sustains itself.
In 1949, American philosopher John Dewey proposed in his book “Knowing and the Known” that the exchanges which take place between all living organisms as well as with their environment are ‘trans-actional’. This means that all reciprocal activity between organisms can be described as mutual, simultaneous exchanges, through which all parties involved are changed in some way. The idea is distinctly opposed to ‘interaction’, in which physical objects are independent of each other, and don’t do anything unless they are acted upon by other objects or forces.
Through her research, Dr Sánchez-Flores argues that this all-encompassing idea of the nature of exchanges between living systems must also apply to the language we use. “According to Dewey, a trans-actional presentation of knowledge means that everything that we seek to explain as observers exists in continuity with everything else”, she describes. “I propose that the autopoietic conception of language is eminently trans-actional in this way. Seeing everything that we want to explain in continuity with everything else discloses the realm of simultaneity.”
Such a concept appears to be at odds with the classical view of the universe. According to earlier thinkers like Newton and Descartes, processes can only take place if they were triggered by separate, previous events. However, the trans-actional, autopoietic interpretation of language isn’t without a physical basis. For a better comparison, Dr Sánchez-Flores looks to a more recent interpretation of physics in which the chain of cause-and-effect is no longer set in stone: the quantum realm.
Human language is a by-product of the relationships that human beings build with one another and on which they depend as organisms to survive, thrive, and emerge as persons.
Quantum entanglement as trans-actional presentation of knowledge
Perhaps one of the most famous and mind-bending consequences of quantum physics is the principle of entanglement, which describes how the fate of one particle can entirely depend on that of another to which it is connected. This would mean that when a scientist observes the state of one particle, the result will determine the observed state of its entangled partner at exactly the same time, even if they are separated by large distances. Additionally, the presence of scientific observation itself alters the outcome of the experiment.
Dr Sánchez-Flores believes that this strange, yet experimentally proven phenomenon is the clearest example of a trans-actional presentation of knowledge. It exemplifies how the notion of independent physical bodies acting on each other and the objective/subjective duality are useful myths or illusions of the Cartesian worldview that is most prevalent today.
As environments present organisms with new problems, their resulting actions to find a solution will change the organisms themselves and their trans-actions will trigger simultaneous change in their environment in turn. “Autopoietic living systems are, at the same time, organisationally closed and structurally coupled to their environment”, explains Dr Sánchez-Flores. “Both Maturana and Dewey see the scientific observer as an organism itself seeking to solve a problem that is underpinned by the organism’s experience and by its need to find equilibrium in its environment.” Simultaneous closure and coupling in body-sized organisms help us visualize how everything is connected to everything else, similarly to quantum-sized particles where this kind of entanglement occurs at a subatomic level.
Overcoming human barriers
Human language as trans-actional autopoiesis could have profound implications for the role which language plays in shaping our understanding of human existence. In comparison to the surrounding environment of a living organism, language represents a trans-actional autopoietic environment which spans the many countless groups we have divided ourselves into over the course of history. Unfortunately, we have become all too familiar with the damaging consequences of the many disagreements, misunderstandings, and prejudices which occur between these groups.
Dr Sánchez-Flores argues that we would be better equipped to heal these divides if we better understood the role which language plays in shaping our species as a whole. Instead of passively observing our surroundings, she proposes, every one of us actively participates in the development of the world as we perceive it as we exchange knowledge with each other. In turn, knowledge of the continually re-shaping world in awareness of simultaneity opens up the possibility of acknowledging the damaging and violent effects of in-group/out-group human barriers in order to heal them.
“This reinforces and supports a trans-actional presentation of knowledge with cosmopolitan possibilities, where human beings are aware of their need for and dependence on one another beyond artificially created borders – such as tribes, ethnic groups, races, disciplines, and nations”, Dr Sánchez-Flores illustrates. “From this, human beings can be made aware of the vital and essential way in which we are all connected to one another, to non-human organisms, and to our environment.”
From the immediate threat of a worldwide pandemic to the long-term consequences of a heating climate, a thorough understanding of the role that language plays in shaping our existence has never been more important.
By viewing the role of language through the lens of trans-actional autopoiesis, Dr Sánchez-Flores believes that our systems of governance would be far better equipped to understand and face these global challenges, and to account for the widely varied needs of the different groups these efforts involve. This would ultimately provide a strong basis for making decisions based on reason, compassion, and equity, all while accounting for a diverse range of languages, worldviews, and ideologies.
Tackling global challenges
Dr Sánchez-Flores believes her ideas come at a crucial crossroads in the story of our species – in which humanity as a whole faces a set of challenges which are more global and all-encompassing than any in its history. From the immediate threat of a worldwide pandemic to the immeasurable long-term consequences of a heating climate, a thorough understanding of the complete role that language plays in shaping our existence has never been more important.
She concludes, “in the current COVID-19 world-pandemic, it is urgent for the human species that a trans-actional presentation of knowledge becomes the new normal, just as caring and compassion have become constant sources of inspiration during this crisis. This cannot be postponed due to the probable emergence of new pandemics and other climate crises that threaten the very existence of the human species.” Ultimately, Dr Sánchez-Flores’ ideas clearly show that just as the exchange of knowledge has enabled us to thrive as a species, it is now the ultimate toolset for dealing with these existentially daunting problems.
What steps do you think world governments could take to implement your ideas into their decision-making processes?
<>Modern states represent one more stakeholder in the realm of global or transnational governance – albeit an essential one as a source of legitimate law. Transnational governance structures may include governments and their agents, but also social movements, Indigenous peoples, grassroots organisations, powerful individuals, as well as corporations. COVID-19 has produced awareness that human beings are connected to each other and their environment, and that borders can be futile. To respond to future pandemics and crises, it is essential to strengthen existing transnational structures of governance to produce essential care and services for people around the world, especially for the most marginalised.


Quantum computers are making all the headlines these days, but quantum communication technology may actually be closer to practical implementation. In a bid to hasten its arrival, researchers have now mapped out the path to a quantum internet.
The building blocks for these emerging technologies are more or less the same. They both use qubits to encode information—the quantum equivalent to computer bits that can simultaneously be both 1 and 0 thanks to the phenomena of superposition. And they both rely on entanglement to inextricably link the quantum states of these qubits so that acting on one affects the other.
But while building quantum computers capable of outperforming conventional ones on useful problems will require very large networks of qubits, you only need a handful to build useful communication networks.
And we’re already well on the way. In a review article in Science, researchers from the University of Delft in the Netherlands outlined six phases of development towards a global network of quantum-connected quantum computers and point out that we’re already on the bottom rung of that ladder.
“We are now at an exciting moment in time, akin to the eve of the classical internet,” the researchers wrote. “Recent technological progress now suggests that we may see the first small-scale implementations of quantum networks within the next five years.”
The main advantages of a quantum communication network over a conventional one are speed and security. Entanglement makes it possible to communicate instantly across arbitrarily large distances in principle. No matter how far apart you put two entangled qubits, acting on one will have an instant and measurable impact on the other.
It’s also essentially impossible to eavesdrop on a quantum conversation. Under quantum mechanics, if you read the quantum state of an object it changes that quantum state, which means the act of intercepting any message encoded in quantum states will immediately change the content of the message.
But the same property that makes quantum communication intrinsically secure also poses a major challenge. It means qubits can’t be copied or amplified, two essential ingredients of classical communication systems.
Nonetheless, working quantum “trusted repeater networks” are already in operation, which the researchers identify as the first step on the way to a full quantum internet. These networks feature nodes that can encode and decode qubits, which are then sent across optical cables or potentially beamed down from space by a satellite.
But because quantum signals degrade the further they travel, it’s necessary to pass messages from node to node to cover longer distances. Each of these handovers is secure, but if two distant nodes need to communicate, then all the nodes in between know the content of the message, and so must be trusted if the message is to remain secure.
To reach the next stage we will need to develop reliable quantum repeaters, the researchers said. This is a device that is able to establish entangled qubits with each node and then rely on quantum teleportation to effectively swap entanglements around so that the two nodes are entangled. A network connected by these kinds of repeaters would allow any node to securely communicate with any other without having to trust any of the intermediaries.
At both these stages, the principle use would be quantum key distribution, which allows two nodes to securely share an encryption key in a way that can’t be eavesdropped on, which can then be used to decode encrypted messages sent via conventional communication channels.
The process of entangling distant qubits is hit and miss at the minute, though, so the next stage will be to create a network that’s able to create entanglements on demand. The main advantage of this kind of “entanglement distribution network” is that it will make the network device-independent, according to the researchers.
After that, the development of quantum memory will allow much more complicated communication protocols that require quantum information to be stored while further communication goes on. This is a major challenge, though, because quantum states rapidly degrade through a process called decoherence. Most technology proposals only hold their states for seconds or fractions of a second, which poses problems for a network whose communication times are longer than that.
But if it could be realized, it would make it possible for simple quantum nodes to send computations to a quantum computer on the network, potentially creating a kind of quantum cloud. It could also make it possible to do things like synchronize distant telescopes to create a single “super telescope.”
Ultimately, the goal is to create a network of fully–connected quantum computers. The first phase of that will be a “few-qubit fault-tolerant network,” in which the quantum computers at each node will not yet be large enough to out-do standard computers. Nonetheless, the fact that they incorporate fault tolerance will mean they will carry out relatively complex computation and store quantum data for significant amounts of time.
And the final stage will come when these quantum computers finally surpass their conventional cousins, making it possible to create distributed networks of computers capable of carrying out calculations that were previously impossible, and instantly and securely share them around the world.
The authors noted that there’s a long road ahead. We need better ways of encoding, storing, and transmitting quantum information, and perhaps even more importantly, we need to build quantum equivalents of our internet communication protocols, something almost entirely lacking today.
But they’re bullish that the first multinode quantum networks will be appearing in the next few years, which will make it possible to test all these ideas and hopefully turbocharge development of a true quantum internet.


The technology that allowed Marty McFly to travel back in time in the 1985 movie Back to the Future was the mythical flux capacitor, designed by inventor Doc Brown.
We’ve now developed our own kind of flux capacitor, as detailed recently in Physical Review Letters.
While we can’t send a DeLorean car back in time, we hope it will have important applications in communication technology and quantum computing.
How did we do it? Well it’s all to do with symmetry. There are many kinds of symmetry in science, including one that deals with time reversal.
Time reversal symmetry is a complex sort of symmetry that physicists like to think about, and relies on the imaginary as much as the real.
Suppose you make a movie of an event occurring. You could then ask: “If I edited the movie to run backwards, and showed it to my friends, could they tell?”
This might seem obvious: people don’t usually walk or talk backwards; spilt milk doesn’t spontaneously jump back into its carton; a golf ball doesn’t miraculously launch backwards from the fairway, landing perfectly balanced on the tee at the same moment as the club catches it.
But at a microscopic level, the story is not that clear. The collision of two billiard balls looks pretty similar in reverse; even more so for the collision of two atoms. A beam of light travelling in one direction obeys exactly the same laws of physics as a beam of light travelling in the opposite direction.
Indeed, the basic equations of physics look essentially the same if we replace time with its negative. This mathematical transformation reverses the flow of time in our equations.
Since the microscopic laws of physics appear to be unchanged under this mathematical transformation, we say the universe possesses time reversal symmetry, even though we cannot actually reverse time in reality. Unlike Doc Brown, we can’t make the clock tick backwards.
There is a conceptual conflict here. At the macroscopic scale, the entropy of the universe — a measure of disorder or randomness — always increases, so that there is an arrow of time.
This is obvious in our everyday experience: a scrambled egg is not reversible. How does this irreversiblity emerge from microscopic laws that are reversible? This remains a mystery.
The circulator circuit
Microscopic reversibility presents an important technological challenge. It complicates the diversion of electronic and radio signals around a circuit.
There are various applications where engineers want electromagnetic signals (such as light or radio waves) in a circuit to behave a bit like cars around a roundabout.
This is pictured below: a signal entering port A of the device should be directed to port B; a signal entering at B should go to port C; and a signal entering port C should be directed to port A, clockwise around the device.
One way to do this is to use a network of amplifiers to switch signals as desired. But there is a profound result in quantum mechanics (the “no cloning theorem”) that means that amplification must always add noise, or randomness, to the signal. Sorry audiophiles: a perfect amplifier is impossible.
If the signal is extremely weak, so that additional noise is intolerable, then noiseless circulation is accomplished with a device called a circulator. Such devices are used to separate very weak signals going to and from sensitive electronics, including in radar receivers, or in existing and future quantum computers.
It turns out a device like this must locally break time reversal symmetry. If we made a movie of the signals coming and going from the circulator, and ran the movie backwards, it would look different. For example, we would see a signal entering port B and leaving via port A, rather than via C.
But most devices in a quantum research laboratory, such as mirrors, beam splitters, lasers, atoms do not break time reversal symmetry, so cannot be used as circulators. Something else is needed.
The practical way to break time reversal symmetry for real devices is to introduce a magnetic field. Like a rotating vortex in water, magnetic fields have a circulation, since they arise from electrical currents circulating in an electrical loop.
The magnetic field defines a direction of rotation (clockwise or counterclockwise) for electrically charged particles and thus for electrical signals. So when physicists say that a device breaks time reversal symmetry, they usually mean that there is a magnetic field about somewhere.
Commercial circulators are an anomaly in the world of electronics. Unlike transistors, diodes, capacitors and other circuit elements, basic materials science means that commercial circulators have not been miniaturised, and are still the size of a coin.
Building them into large-scale integrated microelectronic circuits is therefore a challenge. This will become an increasing problem as we try to fit thousands of qubits on a quantum computer chip, each requiring its own circulator to enable control and read-out.
Our quantum flux capacitor
We have developed a new way of building micrometer-sized circulators that can be fabricated on a microchip.
We figured out how to integrate magnetic flux quanta — the smallest units of magnetic field — with microfabricated capacitors and other superconducting circuit elements, so that time-reversal symmetry can be broken.
This led to our new circulator proposal. As with conventional circulators, there is a magnetic field present. But because we can use just one magnetic flux quantum, our design can be microscopic.
Sadly for history buffs, our design won’t help much in your DeLorean time machine: it doesn’t reverse time. But its magnetic field does break time-reversal symmetry as advertised and we expect these devices will find applications in future quantum technologies.
Even sooner, they may help in high-bandwidth communications environments like mobile phone base stations in very dense populations, or for ultra-high sensitivity radar where every photon of the electromagnetic field counts.


USC scientists have demonstrated a theoretical method to enhance the performance of quantum computers, an important step to scale a technology with potential to solve some of society’s biggest challenges.
The method addresses a weakness that bedevils performance of the next-generation computers by suppressing erroneous calculations while increasing fidelity of results, a critical step before the machines can outperform classic computers as intended. Called “dynamical decoupling,” it worked on two quantum computers, proved easier and more reliable than other remedies and could be accessed via the cloud, which is a first for dynamical decoupling.
The technique administers staccato bursts of tiny, focused energy pulses to offset ambient disturbances that muck sensitive computations. The researchers report they were able to sustain a quantum state up to three times longer than would otherwise occur in an uncontrolled state.
“This is a step forward,” said Daniel Lidar, professor of electrical engineering, chemistry and physics at USC and director of the USC Center for Quantum Information Science and Technology (CQIST). “Without error suppression, there’s no way quantum computing can overtake classical computing.”
The results were published today in the journal Physical Review Letters. Lidar is the Viterbi Professor of Engineering at USC and corresponding author of the study; he led a team of researchers at CQIST, which is a collaboration between the USC Viterbi School of Engineeringand the USC Dornsife School of Letters, Arts and Sciences. IBM and Bay Area startup Rigetti Computing provided cloud access to their quantum computers.
Quantum computers are fast, but fragile
Quantum computers have the potential to render obsolete today’s super computers and propel breakthroughs in medicine, finance and defense capabilities. They harness the speed and behavior of atoms, which function radically different than silicon computer chips, to perform seemingly impossible calculations.
Quantum computing has the potential to optimize new drug therapies, models for climate change and designs for new machines. They can achieve faster delivery of products, lower costs for manufactured goods and more efficient transportation. They are powered by qubits, the subatomic workhorses and building blocks of quantum computing.
But qubits are as temperamental as high-performance race cars. They are fast and hi-tech, but prone to error and need stability to sustain computations. When they don’t operate correctly, they produce poor results, which limits their capabilities relative to traditional computers. Scientists worldwide have yet to achieve a “quantum advantage” – the point where a quantum computer outperforms a conventional computer on any task.
The problem is “noise,” a catch-all descriptor for perturbations such as sound, temperature and vibration. It can destabilize qubits, which creates “decoherence,” an upset that disrupts the duration of the quantum state, which reduces time a quantum computer can perform a task while achieving accurate results.
“Noise and decoherence have a large impact and ruin computations, and a quantum computer with too much noise is useless,” Lidar explained. “But if you can knock down the problems associated with noise, then you start to approach the point where quantum computers become more useful than classic computers.”
USC research spans multiple quantum computing platforms
USC is the only university in the world with a quantum computer; its 1098-qubit D-Wave quantum annealer specializes in solving optimization problems. Part of the USC-Lockheed Martin Center for Quantum Computing, it’s located at USC’s Information Sciences Institute. However, the latest research findings were achieved not on the D-Wave machine, but on smaller scale, general-purpose quantum computers: IBM’s 16-qubit QX5 and Rigetti’s 19-qubit Acorn.
To achieve dynamical decoupling (DD), the researchers bathed the superconducting qubits with tightly focused, timed pulses of minute electromagnetic energy. By manipulating the pulses, scientists were able to envelop the qubits in a microenvironment, sequestered – or decoupled – from surrounding ambient noise, thus perpetuating a quantum state.
“We tried a simple mechanism to reduce error in the machines that turned out to be effective,” said Bibek Pokharel, an electrical engineering doctoral student at USC Viterbi and first author of the study.
The time sequences for the experiments were exceedingly small with up to 200 pulses spanning up to 600 nanoseconds. One-billionth of a second, or a nanosecond, is how long it takes for light to travel one foot.
For the IBM quantum computers, final fidelity improved threefold, from 28.9 percent to 88.4 percent. For the Rigetti quantum computer, final fidelity improvement was a more modest 17 percent, from 59.8 to 77.1, according to the study. The scientists tested how long fidelity improvement could be sustained and found that more pulses always improved matters for the Rigetti computer, while there was a limit of about 100 pulses for the IBM computer.
Overall, the findings show the DD method works better than other quantum error correction methods that have been attempted so far, Lidar said.
“To the best of our knowledge,” the researchers wrote, “this amounts to the first unequivocal demonstration of successful decoherence mitigation in cloud-based superconducting qubit platforms … we expect that the lessons drawn will have wide applicability.”
High stakes in the race for quantum supremacy
The quest for quantum computing supremacy is a geopolitical priority for Europe, China, Canada, Australia and the United States. Advantage gained by acquiring the first computer that renders all other computers obsolete would be enormous and bestow economic, military and public health advantages to the winner.
Congress is considering two new bills to establish the United States as a leader in quantum computing. In September, the House of Representatives passed the National Quantum Initiative Act to allocate $1.3 billion in five years to spur research and development. It would create a National Quantum Coordination Office in the White House to supervise research nationwide. A separate bill, the Quantum Computing Research Act by Sen. Kamala Harris, D-Calif., directs the Department of Defense to lead a quantum computing effort.
“Quantum computing is the next technological frontier that will change the world and we cannot afford to fall behind,” Harris said in prepared remarks. “It could create jobs for the next generation, cure diseases and above all else make our nation stronger and safer. … Without adequate research and coordination in quantum computing, we risk falling behind our global competition in the cyberspace race, which leaves us vulnerable to attacks from our adversaries,” she said.


Scientists have uncovered a mathematical shortcut for calculating an all-important feature of quantum devices.
Having crunched the numbers on the quantum properties of 12,000 elements and compounds, researchers have published a new equation for approximating the length of time the materials can maintain quantum information, called “coherence time.”
The elegant formula allows scientists to estimate the materials’ coherence times in an instant — versus the hours or weeks it would take to calculate an exact value.
“People have had to rely on complicated codes and calculations to predict spin qubit coherence times. But now people can compute the prediction by themselves instantaneously. This opens opportunities for researchers to find the next generation of qubit materials by themselves.” — Shun Kanai, Tohoku University
The team, comprising scientists at the U.S. Department of Energy’s (DOE) Argonne National Laboratory, the University of Chicago, Tohoku University in Japan and Ajou University in Korea, published their result in April in the Proceedings of the National Academy of Sciences.
Their work is supported the Center for Novel Pathways to Quantum Coherence in Materials, an Energy Frontier Research Center funded by the U.S. Department of Energy, and by Q-NEXT, a DOE National Quantum Information Science Research Center led by Argonne.
The team’s equation applies to a particular class of materials — those that can be used in devices called spin qubits.
“People have had to rely on complicated codes and calculations to predict spin qubit coherence times. But now people can compute the prediction by themselves instantaneously,” said study co-author Shun Kanai of Tohoku University. “This opens opportunities for researchers to find the next generation of qubit materials by themselves.”
Qubits are the fundamental unit of quantum information, the quantum version of classical computer bits. They come in different forms and varieties, including a type called the spin qubit. A spin qubit stores data in a material’s spin — a quantum property inherent in all atomic and subatomic matter, such as electrons, atoms and groups of atoms.
Scientists expect that quantum technologies will be able to help improve our everyday lives. We may be able to send information over quantum communication networks that are impenetrable to hackers, or we could use quantum simulations to speed up drug delivery.
The realization of this potential will depend on having qubits that are stable enough — that have long enough coherence times — to store, process and send the information.
While the research team’s equation gives only a rough prediction of a material’s coherence time, it gets pretty close to the true value. And what the equation lacks in precision, it makes up for in convenience. It requires only five numbers — the values of five particular properties of the material in question — to get a solution. Plug them in, and voila! You have your coherence time.
Diamond and silicon carbide are currently the best-established materials for hosting spin qubits. Now scientists can explore other candidates without having to spend days calculating whether a material is worth a deeper dive.
“The equation is like a lens. It tells you, ‘Look here, look at this material — it looks promising,’” said University of Chicago Professor and Argonne senior scientist Giulia Galli, a co-author of the study and Q-NEXT collaborator. “We are after new qubit platforms, new materials. Identifying mathematical relationships like this one points out new materials to try, to combine.”
With this equation in hand, the researchers plan to boost the accuracy of their model.
They’ll also connect with researchers who can create the materials with the most promising coherence times, testing whether they perform as well as the equation predicts. (The team has marked one success already: A scientist outside the team reported that the relatively long coherence time of a material called calcium tungstate performed as predicted by the team’s formula.)
“Our results help us with advancing current quantum information technology, but that’s not all,” said Tohoku University Professor Hideo Ohno, who is currently president of the university and paper co-author. “It will unlock new possibilities by bridging the quantum technology with a variety of conventional systems, allowing us to make even greater progress with the materials we’re already familiar with. We’re pushing more than one scientific frontier.”
The other authors of the paper are F. Joseph Heremans, Argonne and UChicago; Hosung Seo, Ajou University; Gary Wolfowicz, Argonne and UChicago; Christopher P. Anderson, UChicago; Sean E. Sullivan, Argonne; Mykyta Onizhuk, UChicago; and David D. Awschalom, Argonne and UChicago.
This work was supported by the Center for Novel Pathways to Quantum Coherence in Materials, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, in collaboration with the U.S. Department of Energy Office of Science National Quantum Information Science Research Centers.
Q-NEXT is a U.S. Department of Energy National Quantum Information Science Research Center led by Argonne National Laboratory. Q-NEXT brings together world-class researchers from national laboratories, universities and U.S. technology companies with the single goal of developing the science and technology to control and distribute quantum information. Q-NEXT collaborators and institutions will create two national foundries for quantum materials and devices, develop networks of sensors and secure communications systems, establish simulation and network testbeds, and train a next-generation quantum-ready workforce to ensure continued U.S. scientific and economic leadership in this rapidly advancing field. For more information, visit https://www.q-next.org.
Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science.
The U.S. Department of Energy’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit https://energy.gov/science.


NASA quantum computer efforts will combine the space agency’s deep expertise in computing with its scientific ambition.
The National Aeronautics and Space Administration — or NASA — is known as one of the key organizations that propelled humankind’s small steps and giant leaps into outer space. What many do not realize is that NASA scientists were also leaders in efforts to master computers and supercomputers, an expertise that led to computational innovations that went beyond space travel, including advances in structural analysis software and satellite imaging advances.
Now, pioneering NASA quantum computer scientists plan to continue this legacy of scientific exploration to tap the inner reaches of quantum mechanics, work that could build the technologies that may propel humanity farther into space while also helping solve some closer-to-world problems, such as climate change and pollution control.
NASA Quantum Computer History
The history of NASA quantum computer efforts go back decades and are centered mainly in the organization’s Ames Research Center, which coincidentally or not, is located in Silicon Valley. Computational pioneer and Ames center director Hans Mark commissioned the first massively parallel computer at Ames. This computer uses multiple processors at the same time, or in parallel, and this advanced computing device offers a hint at NASA quantum computer ambitions.
Those ambitions led to the creation of the Quantum Artificial Intelligence Laboratory (QuAIL), which is where the organizations conducts research to explore quantum computing and how it might be able to power NASA into the future — and into deep space.
According to NASA, the lab conducts research on quantum applications and algorithms, develops tools for quantum computing and investigates the fundamental physics behind quantum computing.
NASA Quantum Computer Use Cases
Because many of NASA’s duties require large-scale computing efforts, the space agency’s quantum computers could tackle several tasks.
Early versions of quantum computers, such as the Noisy Intermediate Stage Quantum — or NISQ — devices — could be used for planning and scheduling, fault diagnosis and machine learning, according to a NASA research paper. Other use cases would include building robust, secure communication networks and simulating many-body systems for material science and chemistry investigations.
“For the last few years, the NASA Quantum Artificial Intelligence Laboratory (QuAIL) has been performing research to assess the potential impact of quantum computers on challenging computational problems relevant to future NASA missions.”
NASA’s quantum computing projects are going on right now.
According to the authors of the paper: “For the last few years, the NASA Quantum Artificial Intelligence Laboratory (QuAIL) has been performing research to assess the potential impact of quantum computers on challenging computational problems relevant to future NASA missions. A key aspect of this research is devising methods to most effectively utilize emerging quantum computing hardware.”
Quantum sensing is another important use case for NASA quantum computers.
NASA is also researching different quantum computer modalities. The teams are investigating both quantum annealing and gate-model quantum computers.
NASA Quantum Computer — the Partnerships
Not all of NASA quantum computer work is done in house. The administration relies on numerous partnerships throughout the quantum computing ecosystem to investigate and advance NASA’s quantum computing explorations. These partnerships include collaborations with other government research institutions, quantum labs, large corporations and startups.
It is important to note that NASA was part of the team that helped Google establish quantum supremacy in 2019.
Some of the NASA quantum computer partnerships include Google, Oak Ridge National Laboratory, or ORNL and Rigetti. NASA’s QuAIL is also part of two of the Department of Energy’s centers under the National Quantum Initiative, specifically the Co-design Center for Quantum Advantage and Superconducting Quantum Materials and Systems Center.
Rigetti has teamed with partners, including Defense Advanced Research Projects Agency (DARPA) and NASA, to work on quantum computer approaches to scheduling problems.
On that partnership, Mandy Birch, Senior Vice President, Engineering Strategy at Rigetti, said: “We’re honored to be chosen by DARPA and believe we are uniquely positioned to demonstrate quantum advantage for this class of problem. We believe strongly in an integrated hardware and software approach, which is why we’re bringing together the scalable Rigetti chip architecture with the algorithm design and optimization techniques pioneered by the NASA-USRA team.”
Cold atom quantum computer pioneer is also a NASA partner. ColdQuanta’s equipment, for example, are used in the International Space Station.
NASA Quantum Computer — the Future
As NASA’s space ambitions increase, we would expect that its quantum computing ambitions will go — one might even say boldly go — right along with its drive toward deep space. In fact, because quantum computing is in its infancy the administration speculates that NASA quantum computer project will evolve and accelerate rapidly with other missions.
According to NASA: “Quantum computing is a field of study in its infancy. So far, it is too early to implement quantum computing into NASA missions. The role of QuAIL is to investigate quantum computing’s potential to serve the agency’s future needs, for missions yet to be proposed or even imagined.”
There are several directions NASA quantum computer research would be expected to go beyond the day-to-day tasks that those devices could help the space agency. Quantum secure satellites could provide snoop-proof communications for national security groups and the military. NASA’s combined expertise in both quantum computing and satellite technology would make the space agency a natural fit for work to make and launch these ultra-secure systems.
Deep space travel will also require new forms of propulsion and even new space craft designs. NASA quantum computers directed at materials research could assist in analyzing measurements of new types of thrusters, for example. They could also be used to determine what types of materials could be used for space crafts and even custom design materials to the exacting designs required by long-term space travel, for example.


As powerful as quantum computers may one day prove, quantum physics can make it challenging for the machines to carry out quantum versions of the most basic computing operations. Now scientists in China have created a more practical quantum version of the simple AND operation, which may help quantum computing reach successful near-term applications.
Conventional electronics nowadays rely on transistors, which flick on or off to symbolize data as ones and zeroes. They connect transistors together to build devices known as logic gates, which implement logical operations such as AND, OR, and NOT. Logic gates are the building blocks of all digital circuits.
In contrast, quantum computers depend on components known as quantum bits or “qubits.” These can exist in a quantum state known as superposition, in which they are essentially both 1 and 0 at the same time. Quantum computers work by running quantum algorithms, which describe sequences of elementary operations called quantum logic gates applied to a set of qubits.
“Our work will help narrow the gap between the most anticipated near-term applications and existing noisy devices.”
—Fei Yan, Southern University of Science and Technology, Shenzhen, China
Superposition essentially lets each qubit perform two calculations at once. The more qubits a quantum computer has, the greater its computational power can grow in an exponential fashion. With enough qubits, a quantum computer could theoretically vastly outperform all classical computers on a number of tasks. For instance, on quantum computers, Shor’s algorithm can crack modern cryptography, and Grover’s algorithm is useful for searching databases at sometimes staggering speeds.
However, quantum computers face a physical limitation: All quantum operations must be reversible in order to work. In other words, a quantum computer may perform an operation only if it can also carry out an opposite operation that returns it to its original state. (Reversibility is necessary until a quantum computation is run and its results measured.)
In everyday life, many actions are reversible—for example, you can both tie and untie shoelaces. Others are irreversible—for instance, you can cook an egg but not uncook it.
Similarly, a number of logical operations are reversible—you could apply the NOT operation to a variable and then apply it again to return it to its original state. Others are generally irreversible—you could add 2 and 2 together to get an outcome of 4, a mathematical version of the AND operation, but you could not reverse the operation and know an outcome of 4 began as 2 and 2 unless you knew what at least one of the original variables was.
The AND gate is a fundamental ingredient of both classical and quantum algorithms. However, the demand for reversibility in quantum computing makes it challenging to implement. One workaround is to essentially use an extra or “ancilla” qubit for each AND gate that stores the data needed to reverse the operation.
However, quantum computers are currently noisy intermediate-scale quantum (NISQ) platforms, meaning their qubits number up to a few hundred at most and are error-ridden as well. Given quantum computing’s primitive state right now, it would prove “extremely cumbersome to design and build hardware for accommodating extra ancilla qubits on an already crowded processor,” says study cosenior author Fei Yan, a quantum physicist at the Southern University of Science and Technology in Shenzhen, China.
“Our technique presents a scaling advantage. The more qubits are involved, the more cost-saving our technique would be compared to the traditional one.”
Now Yan and his colleagues have constructed a new quantum version of the AND gate that removes this need for ancilla qubits. By getting rid of this overhead, they say, their new strategy could make quantum computing more efficient and scalable than ever.
“Our work will help narrow the gap between the most anticipated near-term applications and existing noisy devices,” Yan says. “We hope to see quantum AND functionality added to quantum programs on machines elsewhere, such as the IBM quantum cloud, and played with by more people.”
Instead of using ancilla qubits, the new quantum AND gate relies on the fact that qubits often can encode more than just zeroes and ones. In the new study, the researchers have qubits encode three states. This extra state temporarily holds the data needed to perform the AND operation.
“We do not use any ancilla qubits,” Yan says. “Instead, we use ancilla states.”
In the new study, the scientists implemented quantum AND gates on a superconducting quantum processor with tunable-coupling architecture. Google also employs this architecture with its quantum computers, and IBM plans to start using it in 2023.
“We think that our scheme is well-suited for superconducting qubit systems where ancilla states are abundant and easy to access,” Yan says.
In experiments, the researchers used their quantum AND gate to help construct Toffoli gates, with which quantum computers can implement any classical circuit. Toffoli gates are key elements of many quantum-computing applications, such as Shor’s and Grover’s algorithms and quantum error-correction schemes.
In addition, with six qubits the researchers could run Grover’s algorithm on a database with up to 64 entries. “To our knowledge, previous demonstrations of Grover’s search on any system was limited to 16 entries,” Yan says. This highlights the way in which the quantum AND operation can help scale up quantum computing, he adds.
All in all, “what we really want to emphasize is that our technique presents a scaling advantage,” Yan says. “The more qubits are involved, the more cost-saving our technique would be compared to the traditional one.”
Although these experiments were conducted with superconducting qubits, Yan notes that their quantum AND gate could get implemented with other quantum-computing platforms, “such as trapped ions and semiconductor qubits, by utilizing appropriate ancilla levels.”
The scientists detailed their findings online 14 November in the journal Nature Physics.
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USC (US) — Researchers have built a quantum computer in a diamond, the first of its kind to include protection against harmful noise called “decoherence.”
The demonstration showed the viability of solid-state quantum computers, which—unlike earlier gas- and liquid-state systems—may represent the future of quantum computing because they can easily be scaled up in size. Current quantum computers typically are very small and, though impressive, cannot yet compete with the speed of larger, traditional computers.
A 20 micron x 20 micron magnification of the diamond chip, showing an integrated diamond lens above the single particle spins where the calculations take place. (Credit: Delft University of Technology/UC Santa Barbara)
The multinational team included University of Southern California professor Daniel Lidar and postdoctoral researcher Zhihui Wang, as well as University of California, Santa Barbara physicist David Awschalom. The findings are published in Nature.
The team’s diamond quantum computer system featured two quantum bits, or qubits, made of subatomic particles.
As opposed to traditional computer bits, which can encode distinctly either a one or a zero, qubits can encode a one and a zero at the same time. This property, called superposition, along with the ability of quantum states to “tunnel” through energy barriers, some day will allow quantum computers to perform optimization calculations much faster than traditional computers.
Like all diamonds, the diamond used by the researchers has impurities—things other than carbon. The more impurities in a diamond, the less attractive it is as a piece of jewelry because it makes the crystal appear cloudy. The team, however, utilized the impurities themselves.
A rogue nitrogen nucleus became the first qubit. In a second flaw sat an electron, which became the second qubit. (Though put more accurately, the “spin” of each of these subatomic particles was used as the qubit.)
Electrons are smaller than nuclei and perform computations much more quickly, but they also fall victim more quickly to decoherence. A qubit based on a nucleus, which is large, is much more stable but slower.
“A nucleus has a long decoherence time—in the milliseconds. You can think of it as very sluggish,” says Lidar.
Though solid-state computing systems have existed before, this was the first to incorporate decoherence protection—using microwave pulses to continually switch the direction of the electron spin rotation.
“It’s a little like time travel,” Lidar says, because switching the direction of rotation time-reverses the inconsistencies in motion as the qubits move back to their original position.
“Although interactions between a quantum bit (‘qubit’) and its environment tend to corrupt the information it stores, it is possible to dynamically control qubits in a way that facilitates the execution of quantum information-processing algorithms while simultaneously protecting the qubits from environment-induced errors,” says Awschalom.
The team was able to demonstrate that its diamond-encased system does indeed operate in a quantum fashion by seeing how closely it matched “Grover’s algorithm.”
The algorithm is not new—Lov Grover of Bell Labs invented it in 1996—but it shows the promise of quantum computing.
The test is a search of an unsorted database, akin to being told to search for a name in a phone book when you’ve only been given the phone number.
Sometimes you’d miraculously find it on the first try, other times you might have to search through the entire book to find it. If you did the search countless times, on average, you’d find the name you were looking for after searching through half of the phone book.
Mathematically, this can be expressed by saying you’d find the correct choice in X/2 tries—if X is the number of total choices you have to search through. So, with four choices total, you’ll find the correct one after two tries on average.
A quantum computer, using the properties of superposition, can find the correct choice much more quickly. The mathematics behind it are complicated, but in practical terms, a quantum computer searching through an unsorted list of four choices will find the correct choice on the first try, every time.
Though not perfect, Lidar and Wang’s computer picked the correct choice on the first try about 95 percent of the time—enough to demonstrate that it operates in a quantum fashion.
“This demonstration of performing a quantum algorithm at the subatomic level with single spins suggests a pathway to build increasingly complex quantum machines, using qubit control protocols that circumvent the expected limitations from real materials,” says Awschalom.
Researchers from Delft University of Technology in the Netherlands and Iowa State University also contributed to the research, which was funded by the National Science Foundation and the U.S. Army Research Office’s Multidisciplinary University Research Initiative.
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