In 1965, Intel’s cofounder Gordon Moore predicted the doubling of computing power every two years through innovations in the classical computer chip. Half a century later, we’ve hit the physical limits to this faithful law. And so, as we faced another brickwall, we invented a new generation of computers to get around this problem
Albeit this time we used the same laws of physics that prevented us from classically progressing any further. Here is everything you need to know about the revolutionary world of quantum computing, and how it will influence our future.
The History of Computing
Relics like the Sumerian Abacus (2500 B.C.) and the Antikythera Mechanism (100 B.C.) were some of the earliest computers that our ancestors invented to make their lives easier. These devices were able to find solutions to problems that involved large calculations and the projections of celestial objects in the sky. Centuries later, computing evolved to incorporate electronic devices that accelerated human life inprovement. Credit for this carries over to the brilliant men and women, like Babbage, Lovelace, Shannon, Turing, Von Neumann, and others who laid the foundation to our modern day computing.
Some say these innovations can be viewed as proof of human intelligence. After all, we don’t see integrated circuits being grown on trees, except if you think about it, leaves do exhibit similar characteristics. And here lies a question that needs to be begged. Are humans really that extraordinary to build computers? The answer I believe is no. I believe these inventions are just further proof of natures inexplicably complex computing models that which remains to date, an elusive but valid source of inspiration. If we observe closely, proof of computation can be found interwoven within our entire physical reality.
Pan-computational philosophers in the field of digital physics, like Weizsäcker, Jaynes, and Wheeler, go as far — or as close to —as describing our universe in sets of information-that is, the building blocks of our reality existing in a matrix of yes-or-no decisions. With quantum leaps undertaken with quantum technology, we are currently approaching a point where we can ultimately put these theories to test. Advances in our materials and tools have enabled us to finally work with a 100-year-old branch of physics known as quantum mechanics. Using our newfound capabilities, we’ve invented new computational models that aid us to circumnavigate Moore’s suffocating law (which defines the limit to classical computing).
The novel method of computing we’ve discovered is quantum computing (Q-computing). Q-computing exploits phenomena and properties observed in quantum mechanics, like superposition, superconductivity, quantum entanglement, quantum tunneling, quantum annealing, spin, and polarization, all of which are observable in particles and small molecules alike.
What is Quantum Computing?
In my expeeience, the most effective method of understanding Q-computing is by drawing parallels between classical computers and quantum computers. To simply state, a classical computer employs a binary system consisting of either “1 or 0” to encode data while a quantum computer (Q-computer) uses quantum bits (qubits) being composed of, in a classical interpretation, a blend of “1 & 0” to encode data. This blend allows a Q-computer with ’n’ number of qubits to occupy ‘2^n’ number of states/combinations all at once as opposed to just one state/combination with a classical computer.
So, if we were to build a quantum computer system being made up of 300 qubits, then we can hypothetically calculate, in a brief amount of time, more steps (1×10⁹⁰) than all the atoms (1×10⁸³) in the observable universe. And all while using a fraction of energy. The unparalleled power of a quantum computer is therefore demonstrated in this example.
Note: The states of qubits are conventionally written in Dirac Notation as either |0>-ket or |1>-ket. Paul Dirac made this notation in 1939 for its usefulness in the field of quantum mechanics.
Today quantum computers exist and can be operated by anyone with an internet connection (links present in the previous paragraph). However, if you are a researcher, scientist or employee of a Fortune 500 company then you may be able to ger access to a more advanced Q-computer early in its testing phase.
Champions of Quantum Computing
Few companies around the world have undertaken the bold step to take on the challenge of building the ultimate Q-computing device. Each month, more and more companies join the this list
D-wave, established in Burnaby, Canada, is one such company which partnered with Google, Lockheed Martin, NASA, Universities Space Research Association (USRA) and Los Almos National Laboratory to make the world’s first commercially viable Q-computer. The D-wave 2000Q system consists of a whopping 2048 qubit quantum processor (QPU) and uses Quantum Annealing to overcome problems of optimization, machine learning and material development.
You can access the computer through the cloud from their website, so go take the leap.
Having mentioned before the inconceivable power of Q-computing with just 300 qubits, what secrets of the universe can we unlock from D-wave’s 2048 qubit system? For the time being, the scientific community has made no special remarks. Whether 2000Q is, in fact, the prophesied technology of wonder that Richard Feynman envisioned (in his leading paper about simulating physics) remains a matter of further research. So far tests to prove its supremacy has not been up to mark and its status as a qualifying Q-computer is, for the time being, in a superposition itself.
This is why companies like IBM, Intel, Rigetti, Alibaba and Google have all taken a more difficult and less contended approach to building a universal QPU. By choosing superconducting qubits over the methods of quantum annealing, they hope to achieve quantum supremacy with fewer qubits having greater flexibility. IBM has been making ripples in the field with its new upgraded IBM-Q 20 Tokyo Universal Q-computer. It offers to its clients from Fortune 500 a 50 qubit prototype as well.
IBM, like D-wave, in addition allows the public to access its 5-bit and 16-bit Q-computer through their cloud.
Future use cases for this technology make it appealing for companies to add it in their portfolio of services over the cloud and devices manufactured for consumers. There is the 16-qubit Aspen-1 by Rigetti, 49-qubit Tangle Lake by Intel, 72-qubit Bristlecone by Google, and a 124-qubit Tai Zheng classical simulator by AliBaba. The race to quantum supremacy is becoming a progressively interesting one as corporations push to surpass classical computers – the same computers that some companies themselves pioneered. Even as you read this article, researchers are working tirelessly to prove their systems have beaten their automaton cousins.
It could also very well be that big companies could lose to smaller research groups and startups that have taken other paths to the same problem. Some of these groups have been:
- MIT, Harvard and CalTech 51-qubit Rydberg Atom device
- University of Maryland (UoM) and the National Institute of Standards and Technology’s (NIST) 53-qubit Trapped Ion device
- IonQ’s 79-qubit Trapped Ion device
All these champions, and others demonstrate the enormous potential in realizing what has been since only a long dream in the making.
It is important to be aware that the objective of these companies to replace classical computing, but rather to complement it. By solving certain problems with algorithms hypothesized to be superior when run on Q-computers, the two systems can be used in tandem with each other.
Few of the fields that Q-computing will categorically impact relate to searching, optimization, secure computing, machine learning, materials science, cryptography, quantum chemistry, sampling, condensed matter physics and quantum dynamics. The challenge that quantum complexity theorists currently face is to discover the class sets of problems that can be efficiently solved by Q-computers (Bounded error, quantum, polynomial (BQP) class). One thing is for certain, current Q-computing models and algorithms do offer a significant boost in solving some types of problems but it falls short of the miracle hypercomputer Oracle that Alan Turing and others envisioned.
As for the algorithms that are superior, there are many programs that gained popularity. Shor’s algorithm for factoring and Grover’s algorithm for database searching are known to be exponentially and quadratically faster than their classical counterparts. They offer not a standalone solution but these algorithms have been able to attract the attention of researchers and inventors in the field of data and cryptography.
The Reality of Quantum Computing
Having now known that Q-computing is a lot faster at certain tasks, it does not open the door of possibility for your next gaming console to be a buffed up playstation-Q. Until obstacles like quantum decoherence and quantum noise (both major engineering challenges that have held Q-computing back) is tackled, and new superconducting materials that operate at higher temperatures are fabricated, we cannot expect these devices to be available at our home. Currently, QPUs run at temperatures colder than space at 15 millikelvins and pressures nearly 10 billion times lower than that of the atmospheric conditions on Earth. These operating conditions require extremely sensitive and expensive components to function.
See how other experiments like the Laser Interferometer Gravitational Wave Observatory is impacting delicate science like Q-computing.
But it does make one stop and question whether Q-computing is following a similar path of commercialization that classical computers went through? Today Q-computers are the size of a small room and are able to compute as efficiently as a decent computer. If we can make further breakthroughs with advanced materials and identify ways to correct errors caused during operations, then we can expect an altogether different future.
Applications of Quantum Computing
Coming over to the more practical side of Q-computing where investors are most interested in, the applications lie on a broad spectrum of industries. Some of the most promising applications are tied with simulating molecules and atoms. As Q-computers are built with small particles they are inherently better suited to mimic particles that are governed by the laws of quantum mechanics.
I’ll be running you through some examples of scientific research, financial technology (fintech) ,telecommunication (telco) and industrial manufacturing below.
Chemistry: Martin Rahm, Assistant Professor in Physical Chemistry at Chalmers University of Technology, recently developed a new scale of electronegativity by finding the average binding energy of the outermost bound electrons using experimental and quantum-mechanical calculations. Text-book redefining research like this can be carried out using Q-computing as one research group from Oak Ridge National Laboratory demonstrated last year by finding deuteron’s binding energy.
Small Molecular Simulations: Researchers at the University of Sydney and IBM have worked out simulations to obtain the ground states of small molecules like Lithium Hydride and Beryllium Hydride – a task that supercomputers can at best approximate. Compounds like Lithium Hydride are important compounds for advanced batteries, which is why car manufacturers like Volkswagen and Daimler have expressed a keen interest in the research field. And as we will see in the future, the ability to simulate molecules will alter chemistry and manufacturing forever.
Pharmaceuticals: In the field of pharmaceuticals, even firms that can afford state-of-the-art supercomputers will be finding Q-computing useful as it delivers a promise that classical computers cannot. Q-computing will open doors to create new potent drugs whose efficacy will be better understood. It possesses the potential to replace the current method of investing billions of dollars on research that requires decades to develop. The turn of this century is expected to witness the emergence of “superbugs”, bacterial strains resistant to all known antibiotics. And the situation will need a speedy front line of defence powered by quantum technology.
Chemical Engineering: In the field of Chemical Engineering, Q-computers have established themselves as a game-changer as millions of dollars are invested by giants like DOW and Evonik. Q-computing has a tremendous potential to revolutionize the way we produce ammonia, a key chemical substrate in manufacturing fertilizers needed to grow the world’s food supply. Since World War I ammonia has been manufactured using the Haber-Bosch process: a low yield and high energy process that consumes nearly 2% of all the energy we produce annually. A considerable improvement can be developed if we can figure out the inner workings of nitrogen-fixing bacteria, which makes ammonia at room temperature. Nitrogenase is one such enzyme found in nitrogen-fixing bacteria that for the past 100 years has been in a shroud of mystery due to its complex structure. But as we see with medicine, Q-computing will assist us to unravel the quaternary structure of this enzyme and describe the enzymatic function of the compound. Being able to fabricate this enzyme will improve the food security status of the world and help conserve companies a ton of energy.
Advanced Materials: Photosynthesis in plants has also been difficult to replicate in laboratories. New research has shown plants perform Q-computing for photosynthesis and with our better understanding of Q-computing we may be able to study these processes more deeply and replicate them better. The prospect of manufacturing new materials for solar cells and high-temperature superconducting materials for efficient electronic devices is immense.
Control-Systems and Modelling: At higher levels of abstractions, Q-computing will be used in modern industries for fault detection and optimization problems for different tasks. Using machine learning and Q-computing together, thousands of databases can be scanned for hundreds of variables to train neural networks like GAN in record time with extreme precision.
Fintech: In fintech it’s expected that Q-computing will cause major disruption as blockchain companies strengthen and defend their systems against the algorithmic power of Q-computing, hedge funds decode the stock market and banks design an impenetrable system for transactions.
TelCo: Communications will become safer overall as a property of quantum communication is that eavesdropping irreversibly destroys information, in this way alerting authorities in case of any breach. Physicists in China have been able to exploit the previously mentioned phenomena of quantum entanglement to transfer encryption keys from Earth to Space.
To sum it up, quantum computing, though challenging, has given noble prospects to researchers and investors around the world and is definitely here to stay. The exciting bit though is yet to come as we find new problems that Q-computing will excel at solving. You can get involved with the quantum computing community following the links below.
Development kits by some of the leading companies are:
- Rigetti’s Forest, D-Wave’s Ocean SDK
- IBM’s QISKIT
- Google’s PlayGround
- Intel & QuTech’s Inspire
- Microsoft’s development kit
- IonQ’s SDK environment.
Update #1: There has been an emergence of companies who have dedicated themselves to tackle certain challenges as the technology emerges into the world.
- QuSoft is a Dutch based company that is set on creating fundamentally new software in the field of Q-computing.
- Project Q Sydney has been engaging in critical dialogue for the peace and security implications of a quantum age.
Update #2: Afterpublishing this article many people have approached me asking how they can work for companies that are working on Quantum Computers. Though I am figuring that out myself, I have come across a Medium article by an IBM researcher Jay Gambetta who has provided details on how people from different disciplines can get involved with IBM(including an email to send your resumes to) or any other related company. Read it here: The Hitchhiking Cat’s Guide to Getting a Job in Quantum Computing. If you are in a similar situation like I am, then I wish you best of luck. 🙂
Update #3: Quantum Machine Learning is really taking off. Read this article from Maria Schuld’s account on Quantum Machine Learning 1.0 and and get a top level view of what is really happening in the field.
Secondly, for anyone who wishes to academically get involved with Quantum Computing and Quantum Information can buy/download Quantum Computation and Quantum Information written by Michael Nielsen and Isaac Chuang. The book is considered a ‘bible’ of the field. Thank you Maria for this!
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