Quantum Computing: Past, Present & Future

From New Media Business Blog

Jump to: navigation, search

Quantum computing is a method of computing that utilizes the laws of quantum mechanics to build machines that take a new approach to processing information. Quantum computers use fascinating principles of quantum mechanics, like superposition and entanglement, to perform computational operations in a fundamentally different way than classical computing. The study of quantum mechanics is concerned with the behavior of particles at the quantum level where the rules of our physical world no longer apply. It describes nature holistically in its most rudimentary form; at the smallest scales of energy levels of atoms and subatomic particles. [1] By harnessing the natural behavior of quantum states, quantum computing may lead to "breakthroughs in materials and drug discovery, the optimization of complex man-made systems, and artificial intelligence." [2]



What is Quantum Computing?


Quantum Computers Explained – Limits of Human Technology

Computers are made up of very simple components completing very simple tasks. These components represent data, process data, and control computing mechanisms. As the technological advancements progressed, these components became smaller and smaller. According to Moore’s law, the number of transistors, the smallest computer component, per square inch on integrated circuits had doubled each year. A transistor is a very small switch that can open or block information coming through, known as bits. A transistor is comparable to a light switch; the switch can be on and allow electricity to power the light bulb, or off and block electricity. Approximately 14 nm or 500 times smaller than a red blood cell, these transistors are combined with other components, like diodes, capacitors, and resistors, to create chips that may be as small as a few square millimeters. [1] Therefore, as a metric of improving computer performance, transistors became smaller and other components, like the computer chip, were subsequently decreasing in size or becoming more powerful.

This continual reduction is not sustainable because the size of transistors would eventually approach the quantum scale and the rules of classical physics would no longer govern the behavior of the components. Strange phenomena occur at the quantum level, like quantum tunneling whereby electrons may transfer over the transistor block. [2] This established a limit to the advancement of transistor size; at some point, transistors would reach a minimum size that could not be decreased without defeating the purpose of the component.

As a result of this limit and various other motivations, scientists began working on using quantum properties to their advantage by modeling and building quantum computers. Rather than using bits of information which are on/off switches expressed as ‘1’ or ‘0’, quantum computers use qubits. Qubits can exist in the classical binary ‘0’ and ‘1’ states, but by the principles of superposition, can exist in both states. Essentially, an operation on a qubit would act on both ‘0’ and ‘1’ values at the same time so it would be like performing the operation on two different values. Compared to a bit, that can only exist as a ‘0’ or ‘1’, a qubit can be both simultaneously. Consequently, adding additional qubits to the system will exponentially increase the possible combinations of states, enabling quantum computers to solve certain problems in a fraction of the time taken by a classical computer.[3]

Quantum vs. Classical Computing

As mentioned above, classical computers rely on bits as the form of information for processors. The processor will take in bits and output information that is the translated into formats that are useful to humans. Classical computers solve problems in sequence by adjusting transistor states, between ‘1’ and ‘0’. Therefore, the classical computer will solve problems in a sequential order of states. To increase processing speed, or process more information in smaller amounts of time, more processors can be added, or the speed at which the CPU draws from or puts information into memory can be improved. These features of classical computing suggest a limitation of the number of possible states, thus, a limit to problem-solving with very complex problems. These problems are called NP-hard problems, which are defined as being at least as hard as the hardest problems in NP (nondeterministic polynomial time). These problems are practically unsolvable; a classical computer would not be able to determine an answer in a reasonable amount of time. [4]

A quantum computer solves problems by using the unique properties of qubits. Qubits are placed in superposition and behave as ‘0’ and ‘1’ simultaneously in entanglement so that the state of one is highly correlated with the state of another. A problem is coded, and a solution is obtained by examining the interference of various results. The process of solving the problem can be thought of as a wave. The initial problem is coded as a certain wavelength. Every possible solution is also a wave and will interfere with the problem. If the solution is in phase with the problem, the amplitude of the wave will increase, magnifying the probability that the answer is correct. If the solution is out of phase with the problem, the amplitude will decrease, minimizing the probability that the answer is correct. Ultimately, the output is a distribution pattern of probable answers. [5]

Quantum Mechanics Concepts for Quantum Computing

An understanding of quantum mechanics concepts prefaces a deep comprehension of quantum computing. A complete study of quantum mechanics topics will not be explained in exhaustive detail; this would require lots of time, numerous thought experiments, and a deep understanding of dense, scientific material. Rather, a select few topics will be discussed in a simplified manner with examples that are based in intuitive knowledge. The necessary topics for a rudimentary understanding of quantum computing are:, wave-particle duality, quantum tunneling, Heisenberg’s uncertainty principle, entanglement, and superposition. As a caution, some examples, for the sake of comprehension, may sacrifice accuracy for clarity. Please visit an explanation of quantum mechanics for a complete account of the concepts discussed below.

Wave-Particle Duality

Double Slit Experiment Explained

Wave-particle duality is a concept of quantum mechanics that describes the behavior of quantum-scale objects. Essentially, as the scale of observation gets very small and approaches the quantum level, the rules of classical physics no longer apply. At the quantum level, a quantum object may exhibit the properties and behaviors of a wave, and sometimes, of a particle. [1] This is best exemplified by a visual of the double slit experiment.

An example of wave-particle duality in a non-quantum level scale may assist interpretation of this concept. For example, when a rock is dropped into the middle of a lake, waves begin at the point of impact and move away in a circular fashion around the center point. Truthfully, the waves are the transfer of energy to the water from the rock, but in this case, consider the waves to be the transformation of the actual particle into a wave. Therefore, the rock enters the water and turns into a wave. Now, consider a stick floating in the lake adjacent to the point where the rock was dropped. When the waves from the impact reach the stick, the rock pops out. This example demonstrates the oddities of physics at the quantum level.

Quantum Tunneling

Quantum tunneling is a concept of quantum mechanics that describes the ability of quantum objects to pass through barriers that, in classical physics, it should not be able to overcome. This is a result of wave-duality because quantum objects behave as both waves and particles and can, therefore, approach barriers as a particle and tunnel through as a wave. In computing, this creates a physical limit to the size of transistors; they can only get so small before quantum tunneling may occur and allow electrons to tunnel past barriers. [2]

For example, imagine throwing a tennis ball against a window. The expectation is that the ball will bounce against the wall and return towards the direction it was thrown. Perhaps with enough power, the tennis ball could be thrown through the window by breaking the glass. However, at the quantum scale, the ball can be thrown through the window without breaking the glass. It approaches the window as a particle, moves through the window as a wave, and emerges as a particle on the other side.

Heisenberg's Uncertainty Principle

Heisenberg's Uncertainty Principle Explained

The uncertainty principle is a concept of quantum mechanics that describes a limit to the precision of knowing and measuring the properties of complementary. variables[1] The principle suggests a zero-sum outcome. By attempting to precisely measure the physical properties of one variable, the measurement of the physical properties of the complementary variable become less precise. When trying to measure position and momentum, for example, the more specific the measurement of position, the more uncertain the measurement of momentum. For example, an observer wants to measure the position and momentum of a car traveling at a constant velocity from one intersection to the other. To measure momentum, the observer truly needs to determine the mass and velocity of the car. However, for the sake of simplicity, the observer only needs to measure the velocity. So, the observer moves to a position very close to the car so that she can observe the time it takes to pass between a very small distance. She records, with great precision, the velocity of the car. However, given that she is so close to the car, she does not know the car’s position. She would not be able to determine the position of the car relative to other objects in space. On the other hand, if she were in a helicopter, she could measure a precise position of the car, but would not be able to accurately determine the velocity.


Superposition is "the ability of a quantum system to be in multiple states at the same time." [2] The principle states that whenever we do not know the state of a quantum object, that object has the possibility of existing in all states at the same time. However, upon observation, the quantum system collapses into one state. For example, a qubit can be a ‘0’ or a ‘1’ simultaneously. Or, an electron can be spinning in all directions. When we observe the qubit or electron, we will only observe one state. This phenomenon is counter-intuitive to our interpretation of the world; it does not make sense that something can be A or B or C at the same time. Again, this is an example of the distinction between activities at the quantum level and classical level.


Quantum entanglement is the strong correlation between two or more quantum particles that link them together. Particle groups are generated in such a way that the quantum state of each individual particle is interdependent on the quantum states of the other particles. Physical properties like position, momentum, and spin, can be correlated within entangled particles. Entanglement is a state that, if undisturbed and unbroken, will exist across large distances. For example, two electrons are entangled, and electron A is spinning up and electron B is spinning down, if electron B starts to spin up, electron A will start to spin down. However, if entanglement is broken, the system will decohere and both electrons will behave independently.

Summarizing Quantum Mechanics for Quantum Computing: Thought Experiment

Schrodinger's Cat. [3]

The quantum mechanics concepts necessary for an understanding of quantum computing can be illustrated by an iteration of the Schrodinger’s Cat thought experiment. Consider two closed boxes, each containing a cat and a closed can of cat food. The can of cat food can only be opened if a specific particle is inside the box; if the particle is in the box, the can will open, and the cat will eat. Both boxes are placed beside each other and the particle is placed between the boxes. The particle is energized so that it bounces in between the boxes. Due to quantum tunneling, the particle will eventually tunnel through the barrier of one of the boxes, thereby, opening the can of cat food. After waiting some time, you look in between the boxes and sure enough, the particle isn’t there anymore; it has tunneled into one of the boxes. Now, the boxes are entangled because the state of one box is interdependent on the state of the other. One box is taken and put on a space shuttle to the moon while the other box remains on the Earth. At this moment, both boxes are in superposition; the cat within the box could be fed and happy, or irritated and hungry.

Once the space shuttle lands on the moon, the astronaut and you communicate with each other so that you both open the box at the same time. As soon as the box is opened, superposition collapses into one state; fed or not fed. You look inside, and a happy cat is staring back at you. Therefore, the cat in the box on Earth contains the particle and the cat was able to eat the can of cat food. You also know that, at this exact moment, the astronaut on the moon is dealing with a very unhappy cat. You know, considering that both boxes were opened at the same time, at that exact moment of observation, the entanglement was broken. The state of one box is no longer dependent on the state of the other. Perhaps the astronaut wanted to appease the cat and opened the can of food.

Now, you want to make sure that your cat only ate the food and didn’t consume any of the paper labelings on the outside of the can. You feel the cat’s throat for any lumps; you don’t feel any. But you aren’t 100% sure. So, you decide to take an x-ray. You look at the x-ray and it comes back negative, so no paper lumps were found. However, the x-ray gives no indication to the color of the cat’s fur. Therefore, based on the uncertainty principle, the more you tried to measure one complementary variable, the less you knew about the other.

Quantum Computers

Building a Quantum Computer

Internal Components of a Quantum Computer. [4]

Quantum computers require a model of the quantum system that we can control. The current industry norm uses superconductors in room-sized refrigerators cooled to 0.015 Kelvin which is just above absolute zero, or the point at which molecular movement ceases. Liquid nitrogen and liquid helium are used to cool the superconducting qubits so that they stay in a quantum state while performing computational tasks. Otherwise, error rates would increase, and results would be incorrectly presented on the distribution pattern.[5]

Extreme precautions are taken to create and preserve the quantum state. The quantum states are in complete isolation. Any introduction from the external environment like heat, motion, or electromagnetic waves, could cause the quantum states to collapse. This complex operational property intuitively suggests that very few organizations have the resources to maintain and operate a quantum computer. Also, every additional qubit adds more complexity to the quantum system and requires more maintenance.[6]

There are three different types of qubits: flux, charge, and phase. They rely on a superconducting Josephson junction, which is a man-made component on a micro-chip paired with a microwave resonator. The microwave is used to communicate with the qubits.[7]

Different Types of Quantum Computing

Double Slit Experiment Explained

Quantum Annealing

This is the least powerful and most restrictive quantum computer, and consequently, the easiest to build. Quantum annealing is very different from universal gate quantum computing; the two computing methods are not competitors. Instead, they both share the use of fundamental quantum mechanic properties but exploit those advantages to different levels of complexity. A quantum annealing machine is designed to solve objective functions by applying quantum fluctuations. [1] These problems are more commonly known as optimization problems. [2] For example, a common optimization problem is the travelling salesperson problem. A salesperson needs to find the shortest possible route to visit all of his clients before returning to the origin. This seems like a simple problem but is inherently difficult. As more clients are added to the route and variables like time, distance or traffic, are included in calculations, the optimal solution may be practically unsolvable.

The reason that these optimization problems are significant is due to the existence of local minimum or maximum points. These are points that seem to represent the best solution within a range, but not in totality. This is best illustrated by imagining a mountain range. There are many different high points within a given range, however, there can only be one highest point. Classical computers might produce an answer that is locally optimized due to the constraints of processing power within a reasonable amount of time. On the other hand, a problem is coded into a quantum annealer as an "energy landscape" and the absolute highest or lowest points are determined by harnessing the power of entangled qubits in superposition. [3]

Currently, D-Wave has developed a 2000 qubit quantum annealer, the D-Wave 2000Q. [4]

Analog Quantum

The analog quantum computer can simulate complex systems of quantum interactions. Also known as an analog simulator, this machine will be able to solve problems like quantum chemistry, material sciences, optimization, sampling, and quantum dynamics, faster than any classical computers. [5] For example, molecular simulation, which is very difficult due to multiple quantum properties acting within each molecule, may be possible.

Initially proposed by Richard Feynman in 1982[6], an analog quantum machine has functionalities that are in between the quantum annealer and the universal quantum computer. As mentioned, the analog quantum machine is specifically designed to model nature and quantum states that dictate its existence. This is because the complexity of quantum states tend to increase exponentially; even the strongest classical computers are unable to simulate anything more than low-complexity natural states. [7] Therefore, due to the unique computing properties of analog quantum computers, the modeling of nature and its quantum states might be possible.

The current state of quantum computing is somewhere between analog quantum and universal quantum. Analog quantum computers are estimated to be comprised of 50 to 100 qubits in superposition. Notably, Google has developed Bristlecone, a 72-qubit processor [8], IBM offers a 16-qubit cloud processor and has developed a 50-qubit processor [9].

Universal Quantum

The universal quantum computer is the true challenge of quantum computing. This quantum computer would have the largest computational capabilities and would outperform all classical computers. This point, where quantum overtakes classical, is called quantum supremacy. It's the point at which quantum computers will say, "Anything you can do, I can do better." [10] Universal quantum is currently a theoretical model of the first quantum computer to harness the complete power of quantum mechanics for computational and processing purposes. [11]

History of Quantum Computing and Quantum Mechanics

Double Slit Experiment Explained
  • 1900 - Max Planck discovers Planck’s radiation law that suggests the concept of energy quanta, the concept that describes energy as being expressed in discrete levels rather than a continuous spectrum. This discovery is often called the origin of quantum mechanics and represents the old quantum theory or the idea that acceptable energy increments were specific quantities of energy valid at an atomic scale. [1]
  • 1914 - World War I slowed down the progress of quantum theory.
  • 1925 - Werner Heisenberg, Max Born, and Pascual Jordan write a theory of quantum mechanics that formulates matrix mechanics or quantum jumps [2]
  • 1926 - Erwin Schrodinger introduces a wave equation that suggests directed valence bonds, a mathematical distribution of a change of an electron distributed through space. This represents a convergence of opposing quantum theories of the time.
  • 1927 - Werner Heisenberg formulates the quantum uncertainty principle and concludes that quantum theory is concerned with probabilities, not certainties. Many scientists, including Albert Einstein, are skeptical of the probabilistic nature of quantum theory. Quantum experiments don’t produce a definitive answer, rather a probabilistic distribution of possible answers.[3]
  • 1935 - Schrodinger develops the famous Schrodinger’s cat thought experiment which demonstrates the concept of superposition. A cat is placed in a box with a radioactive particle that may decay, killing the cat. However, the particle may also not decay, and the cat would remain alive. The state of the cat is both dead and alive until one opens the box and looks inside. [4]
  • 1959 - Richard Feynman gives a famous lecture at Caltech, There’s Plenty of Room at the Bottom: An Invitation to Enter a New Field of Physics. Feynman postulates the possibility of using the concepts of quantum mechanics to improve computational abilities.[5]
  • 1973 - Alexander Holevo states that n number of qubits cannot carry more information than n classical bits. However, n qubits represent exponentially more states than n classical bits.[6]
  • 1981 - Richard Feynman gives a lecture at MIT for the First Conference on the Physics of Computation. He suggests that classical computers would be unable to simulate the evolution of quantum systems in a meaningful way; quantum systems are too complicated to be computed in a realistic time frame by a classical computer. Therefore, he introduces a model for quantum computing that would be capable of quantum simulations.[7]
  • 1994 - Peter Shor discovers an algorithm or a set of rules, that would allow quantum computers to factor large integers faster than classical computers. This is significant because modern encryption is the multiplication of large prime numbers. The product is the public key; the initial set of prime numbers is the private key. Theoretically, Shor’s algorithm could break modern encryption in a fraction of the time it would take for classical computers. This led to a large increase of interest in quantum computing.[8]
  • 1998 - The first quantum algorithm is computed on a 2-qubit quantum computer at Oxford University.[9]
  • 2011 - D-Wave develops a quantum annealing quantum computer and introduces D-Wave One to the market, the first commercial quantum computer.[10]
  • 2017 - D-Wave introduces the D-Wave 2000Q quantum annealing quantum computer. [11]
  • 2018 - Google introduces “Bristlecone,” a 72-qubit quantum chip.[12]

Current Projects & Applications

Molecular Comparisons

Biogen is a multinational biotechnology company in Cambridge, who focuses mainly on neurological therapies for complex diseases. The company is responsible for numerous research discoveries within the field of diseases such as Alzheimer’s, multiple sclerosis, Huntington’s, etc[13]. Accenture labs is a very large global consulting management firm situated all over the world, specializing in research and developmental areas. Finally, 1QBit is a software and technology development company based out of Vancouver. Their main goal is to try solving industry problems by showcasing the strengths of quantum computing and how they can be used in different industry to optimize them. These three companies came together to develop an improved quantum-enabled molecular comparison application. This application allowed researchers to predict and increase positive effects while minimizing the negative effects of a therapy/drug. Using quantum computing, the researchers were able to complete the complex calculations required for these molecular comparisons at a much faster rate. [14]

To get a better understanding of how quantum computing can improve research in the molecular comparison field, we need to consider what makes the field’s requirements so computationally daunting.

The picture to the right is a nitrogenase enzyme, a very important enzyme that is found in most foods. Looking at the F-cluster selected from the enzyme we can see it’s made up of 3 iron atoms and 4 sulfide atoms. With classical computing, this 7-atom cluster is "the biggest of those iron sulfide clusters that we can simulate on the biggest super computer," according to Dr. Gershon [15]. The reason for this is, every atom expends electrostatic force which pushes and pulls in different ways each atom depending on what other atoms are present [16]. As you add more atoms, every push becomes exponential as it causes a further effect on every other atom [17]. This leads to a huge calculation that quantum computers would be able to calculate in a short period of time compared to classical computers.

Traffic Optimization

Beijing Highway to The Airport. [18]

D-Wave & Volkswagen

In 2017 D-Wave Systems, a Vancouver-based quantum computer engineering company, teamed up with German car manufacturer Volkswagen to address a traffic optimization problem. According to the data company Inrix, the average US commuter spends "42 hours in traffic annually which costs approximately $1,400 in gas" as the engine is left idle. [19]

To try to show how quantum computers could be used to optimize a problem D-Wave used the T-Drive dataset that could be downloaded for free from the Microsoft website. The dataset included 10,357 taxis, 15 million data points and 9 million kilometers of total distance. Using this dataset, D-Wave focused on a specific route which included 418 cars and was heavily congested along a highway from one location of the city to the airport as can be seen below. The 418 cars give us a problem space of approximately 3 to the power of 418, a massive problem to calculate.[20]

To solve the above problem D-Wave team first divided the problem into three steps. Firstly, they had to frame the problem into a grid that was comprehensible by a computer. This meant that all the streets were laid out simplistically on a grid allowing the computer to make decisions more easily. Next, the team had to create a cost function to allow the algorithm to keep tracking of the most efficient street route each car can take. Lastly, the system set constraints to ensure only one route was used for each car.[21]

Below is a comparison of the traffic before and after it was optimized. The quantum computer spread the traffic out to minimize congestion while minimizing the amount of time to arrive at the car’s destination. D-Wave completed this test in 2.5 months and identified areas it would like to improve on in the future. [22]

Before and After Traffic Optimization. [23]


  • Differentiate between different types of streets. The current system did not consider the difference between alleyways, streets, highways, etc.
  • Residential zones. Allowing the system to identify residential zones will allow it to take into account the speed restrictions imposed in those areas.

Dataset Improvements

The team hopes to use data that is constantly changing. The current dataset was static as the cars were not moving, a new data set with constantly moving cars would be more realistic as it would force the computer to constantly recalculate each cars trajectory. Lastly, the team hopes to include more cars in the dataset, starting with 418 cars is an unrealistically small amount so they hope to use more realistic numbers in future experiments.

The above improvements were specified in the VW slideshow on D-Wave's website found at [24].

The Future of D-Wave Systems & Volkswagen

At this moment in time, Volkswagen and D-Wave plan to continue to refine their optimization and find new ways to implement it into different industries. D-Wave is also assisting in the development of new batteries that will last for extended periods of time. These batteries will most likely be used in electric cars produced by Volkswagen in the future. [25]

Online Gaming

Battleships UI. [26]

Quantum Battleship

Quantum Battleship is the world’s first quantum multiplayer game. A simple version of Battleships runs on IBM’s cloud-controlled quantum computer using ProjectQ (that we all have access to online). The main difference between this game and its classical counterpart is the inherent quantum nature the game possess within its attributes. In the traditional battleship, each person will select the locations of their ships on the board and their opponents will attempt to guess their location and destroy the ships. In this sense, the quantum version of the game is very similar with each person selecting one of six locations to place their battleship and their opponent having three attempts to destroy it by selecting one of the six locations. In traditional battleships, if the person guesses the correct coordinates of their opponent’s battleship, the ship will be destroyed, however in the quantum version although you may guess the correct position the ship may not be destroyed or may be completely destroyed. The reason for this lies in the concept of entanglement. Every game created makes "1024 pairs of 0’s and 1’s," therefore "If they agree all the same, we say that the ship is 100% intact. If they disagree all the time the ship is said to be 100% broken" [27].

Therefore, when dropping a bomb, you are simply pushing the 0’s and 1’s around which affects the entanglement or it might not. We can’t be sure until we get our result or “look in” as we would with any other quantum algorithm. The ship can be thought of as both completely intact and complete destroyed at the same time and the result will only be decided once we view the result. [28]

Future Projects & Applications

The Blockchain

MIT describes a blockchain as "a mathematical structure for storing data in a way that is nearly impossible to fake. It can be used for all kinds of valuable data." [29]. It uses standard cryptographic methods to encrypt any data that is stored within it (. Currently, some of the data stored with these functions are shipping data, smart contracts, etc. This brings us to the question of what is encryption? [30]


Encryption is the process of encoding data so that it cannot be understood without an encryption key. For example, when an email is sent from your computer to a friend, the email is encrypted into a jumble of letters, numbers, and symbols that mean nothing to anyone who might intercept the message before reaching the intended recipient. Once the recipient receives the email, they can decode the jumble of symbols into the original message using the encryption key. [31] A classic computer can break this by trying each symbol one by one until it finds the correct combination of symbols, numbers, and digits to decrypt the message in a brute force attack. This, however, will take a very long time to do with if you use a strong enough encryption key. [32]

Quantum computing posing a new threat, using the different qubits within the quantum processor, the quantum computer can try all or a larger amount of different combinations at once to break the code. Which means quantum computers could crack encryption like this in minutes.

Fight Quantum with Quantum

In response to this risk, Rajan and Visser from the University of Wellington in New Zealand, have proposed we fight the quantum problem with a quantum solution. Specifically, by entangling two quantum particles in time and adding it as a layer of security within the encryption. Due to the incredible fragility of the entanglement, any interference with the entanglement or attempts to break the encryption will break the entanglement and instantly invalidate the user out of the system. Although this is a completely theoretic method of security, it proves a new type of thinking that’s coming to the computing world for the future. To cumulatively increase the outcome. [33]

Another way to overcome this would be to use two-factor authentication. No matter how quickly a hacker is able to break one system’s security, it’ll be much harder to overcome breaking the second device in a different location or network. Obviously, as time passes, the technology may advance to the point of breaking two factor, but as it stands it seems unlikely.

New Kind of Internet

With the combination of cryptography and blockchain, loosely-named quantum communication is one of the most interesting, yet theoretical applications for the future of quantum computing. Researchers in China, as well as other countries in the world, have begun researching the potential creation of quantum networks using the same quantum mechanic principles that are used to create quantum computers. The creation of these new networks could mean the potential possibility of a quantum internet. Essentially, on a quantum internet, information would be stored and transmitted through advanced cryptography meaning that the network could be uncrackable. However, this concept is limited by the scalability of the current quantum computers. Largely due to cooling costs, the size of quantum computers, and the undeveloped nature of the technology, any network of useful and meaningful magnitude will not be attainable until quantum computers are widely adopted. [34]

Artificial Intelligence

The basis of artificial intelligence is to create machine learning that rivals the learning capabilities of the human brain. Roger Penrose, the co-author of Stephen Hawking’s famous black hole paper, believes that human consciousness is a direct result of quantum physics occurring in tiny microtubules inside of our brain’s neurons.[35]

The theory basically states that consciousness is very unpredictable. No two humans will experience life the same way due to the infinite number of choices we face daily. Given these circumstances, it would be impossible to predict what any person would do.

If quantum physics is a force that gives us consciousness, the potential for creating consciousness for machine learning through quantum artificial intelligence is a possibility that cannot be ruled out. [36]

Optimization/Simulation Problems

An optimization problem occurs when you are trying to find the best combination of things given some constraints. While problems with only a few choices are easy and can be calculated with a classical computer, as the number of choices grows exponentially, they quickly get very hard to solve optimally. Some of the toughest problems in the world are optimization problems because our current computers cannot solve them as fast as we need them to, quantum computing would help us solve these problems. Some other industries it would benefit are…. supply chain and logistics, financial modeling, cancer radiotherapy, airline scheduling, mission planning. [37]

Quantum and Chemistry


Beryllium hydride is two hydrogen atoms along with one beryllium atom. Right now, however, it is the largest molecule that has ever been modeled on a quantum computer. Scientists programmed an algorithm in the quantum computer to calculate the ground state of all 3 molecules and were successful. [1]

Quantum computers will help us model molecules which could potentially lead to the invention of new drugs and medicine for which we can simulate the effects on our body. Right now the most classical computers can do and this is like the top supercomputer is a couple hundred atoms, say if quantum computers were able to simulate thousands of atoms it would help us understand the effects of these drugs on our bodies and potentially allow us to cure diseases that have never been curable. [2] [3]

Alternative Computing & Processing

Chaos Computing

Chaos computing uses chaotic elements to simulate logical operations. It can generate large numbers of patterns of behavior and are irregular because they switch between these patterns. They display sensitivity to initial conditions which, in practice, means that chaotic systems can switch between patterns extremely fast. The benefits of chaotic computing are that it can be reconfigurable in real-time and possibly be able to perform multiple operations at the same time. [4] [5] [6]

Mem Computing

Currently, classical computers store data and solve problems in two completely different areas. Data is stored in the memory and problem solving is done in the central processing unit (CPU). The inefficiency exists between the data transfer back and forth between these two units. A memcomputer at its core reduces these inefficiencies by storing the data and processing it in the same place using memprocessors. [7]

Biological Computing

Biological computers are based on how cells work in our body. Cells store information and then call upon that information with incredible speed when an external stimulus triggers the activation of that cell. In a biological computer, you can program the cell and have it carry out the operations you need. There is another type of biological computer that focuses on medical based applications by using DNA and RNA to monitor the bodies activities. [8] [9]


SWOT Analysis of Quantum Computing.

Quantum computing is a revolutionary method of computing and processing. It will allow society to solve a wide array of problems that would be practically impossible for classical computers. It will redefine the ways in which we frame problems, conduct research, optimize solutions, etc. The power of quantum computing provides an opportunity for humanity to explore the most natural and rudimentary phenomena and will reinvigorate the curiosity of the natural world. However, quantum computing is without its limitations and problems. The cost of the system may create further wealth disparities; powerful organizations will be able to purchase and use quantum computers which creates a huge competitive advantage. It will be the responsibility of government and powerful organizations to determine the extent to which these advantages are able to remain consolidated within private organizations.

Ultimately, the technology is still in its infancy. Despite all the progress and projects that have been enabled by quantum computers, there is still much scientific debate over the feasibility of developing quantum computers that will achieve quantum supremacy or the point at which a quantum computer outperforms the strongest classical supercomputers. The skepticism of scalability and feasibility of quantum processors is very legitimate. However, like all technological innovation, as public awareness increases, so too will R&D investment. Only time will tell.


Tenzin Ozaki Ramanan Alvapillai Shaihak Sundrani
tozaki@sfu.ca ralvapil@sfu.ca ssundran@sfu.ca
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada


  1. http://www.sciencemag.org/news/2017/09/quantum-computer-simulates-largest-molecule-yet-sparking-hope-future-drug-discoveries
  2. https://www.chemistryworld.com/feature/quantum-chemistry-on-quantum-computers/3007680.article
  3. https://www.youtube.com/watch?v=qarc7AA4-wM&feature=youtu.be
  4. https://en.wikipedia.org/wiki/Chaos_theory
  5. https://en.wikipedia.org/wiki/Chaos_computing
  6. http://www.novaspivack.com/science/chaotic-computing-alternative-to-quantum-computing
  7. https://www.popularmechanics.com/technology/a16308/memcomputer-quantum-computing-alternative/
  8. https://www.extremetech.com/extreme/232190-how-mits-new-biological-computer-works-and-what-it-could-do-in-the-future
  9. https://www.omicsonline.org/biological-computers-their-mechanism-2155-952X.1000122.php?aid=3200
Personal tools