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.

A computational complexity diagram representing the BQP class with other classes

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.

EDSAC (1949) was the size of a room but could perform 650 instructions per second. University of Cambridge

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.

QuTech’s Quantum Vision Team with a dilution refrigerator

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.

IonQ’s ion trap quantum processor

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:

The Composer(graphical user interface) of IBM’s quantum programming software accessible through the cloud.

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: After publishing 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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About the author

Rayyan is an Ontology Engineer working for a startup in San Francisco. His work revolves around complex adaptive systems, systems thinking and software languages. You can mail him your thoughts and views at, connect@rayyanzahid.com.

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