Basics of Quantum Computing
Quantum Computing is an emerging technology designed to perform complex computations in a fraction of the time it takes a classical supercomputer. Underneath this promise lies a solid technological, engineering, and scientific value proposition that can disrupt existing markets and support the emergence of new socio-technical systems that were previously unimaginable.
Quantum computing is “an area of computing focused on developing computer technology based on the principles of quantum theory, which explains the behavior of energy and material on the atomic and subatomic levels.” (FRANKENFIELD, 2019) In layman’s terms, Quantum Computing uses the foundations of quantum theory and quantum mechanics to solve many types of computing problems – faster.
In order to understand the capabilities of Quantum computing, there must be an understanding of quantum mechanics. Quantum mechanics is what makes quantum computing possible – it is analogous to what electricity is for classical computers. Quantum mechanics is the study of motion and interrelation between subatomic particles that explains how energy works at the subatomic level. Some of the fundamental concepts in this area are “quantum entanglement, principle of uncertainty and wave-particle duality” which standard/accepted physics has not yet explained. Arguably the most interesting aspect of quantum mechanics is that some of the activities which occur at the subatomic level lead to unexpected events (e.g. negative mass). To some extent, it is in that uncertainty in which the possibilities for applying quantum computing expand.
The second foundational aspect of quantum computing is the concept of a qubit. A qubit is “the basic unit of quantum information—the quantum version of the classical binary bit physically realized with a two-state device. A qubit is a two-state (or two-level) quantum-mechanical system, one of the simplest quantum systems displaying the peculiarity of quantum mechanics.” (Wikipedia, n.d.) In other words, a qubit represents a continuum of possibilities. To be clear, both a classical “bit” and a quantum bit (“qubit”) contain one unit of information on their own. However, unlike the bit classical computers have, qubits don’t just have a binary option (0 or 1, “on” or “off”), they can exist in either of those states or both…at the same time and on any plane (another term for this is superposition). Furthermore, a qubit has many unique properties which propel both it’s processing power (it is, after all, a computer) and operational abilities.
To expand on those unique properties, we must examine the concept of entanglement. Entanglement allows qubits to multiply their power by enabling qubits to share information (even at great distances). This phenomenon describes how knowing something about one qubit gives rise to information about another – a sort of entangled history exists between qubits which “give definite mathematical and experimental meaning to the proliferation of “many worlds” in quantum theory and demonstrate its substantiality.” (Wilczek, 2016). This sharing of information between qubits is thought to occur almost simultaneously based on observable experiments, but the exact way in which entanglement happens is not fully understood. Entanglement is how qubits (and more importantly the digital information they contain) can more efficiently “communicate” with other qubits, share information, and (in the context of potential applications) solve operational problems much faster than classical computers.
Superposition and Entanglement are arguably two of the most important and well known features of Qubits which make them so special, but there are many others. Another feature is non-locality which is the notion that a qubit knows (almost in real-time) whether another qubit is entangled no matter the distance. Non-locality partially explains quantum communication and is important because it eliminates the criteria of having qubits in close proximity in order for them to work together.
There are some challenges however with the notion of non-local quantum mechanics. For one, there is nothing that has been observed to actually travel non-locally so it’s not possible to send information from one qubit to another in this manner. How then are qubits thought to instinctively know information about another qubit? One theory is that qubits send information from the place where they originally decayed, which, observably is local. The idea is that qubits which have a common origin but were later separated can actually have a stronger correlation than particles which would be considered local in the traditional sense. There are many theories about how measuring the particles of qubits affects the way in which they later communicate, but non-locality has not been readily observed and as a result, proven. The non-observable nature inherent to non-locality is a bit difficult to accept since it defies what we know about traditional physics and is based on the premise that somehow there is a connection that exists that isn’t limited by time or space. This is one of the reasons Einstein referred to this kind of behavior in physics as “spooky action at a distance.”
Aside from their key features, qubits find power in numbers. A qubit by itself isn’t very useful. Sure, it contains more data than a classical bit and perhaps it’s smaller, but that alone doesn’t create a powerful quantum computer. Their power comes from the unique features they possess. One qubit can exist in two states as previously mentioned, but because of superposition, those two states can quickly multiply: 1 qubit can be in a superposition of 2 states, 2 qubits can be in a superposition of 4 states, 3 qubits can be in a superposition of 8 states and so on. As the number of qubits grows, they share exponentially more information precisely because of the aforementioned unique features they contain. This theory however, only applies if the error rate for the qubits is low. The error rate for a qubit is defined as the “probability of undesired change in the qubit state.” (Tannu) In simple terms, quantum errors result in incorrect computational data. As of today, the “ the best two-qubit quantum gates (similar to a basic quantum circuit) have an error rate of around 0.5%.” By contrast, the classical computer has an error rate hovering around “1 error every 10^17 operations.” (Hartnett)
So how do qubits, entanglement, quantum mechanics all come together in the form of a computer? How is a quantum computer built? Qubits are essentially artificial atoms which are built in such a way that they can harness quantum mechanics. That qubit is made out of a superconducting Josephson Junction connected to a microwave resonator. In order for the atom/qubit to remain stable, it requires a temperature of 0.015 Kelvin which translates to -459.7°F - it’s colder than outer space! The microwave resonators “talk” to the qubits. In a lab setting, quantum computers have microwave cables that allow researchers to physically probe the qubits with microwaves.
State of the Art
Quantum computing doesn’t solve real world problems, yet. The main reason is because it is quite difficult to build a quantum computer capable of solving problems more complex than a classical computer can solve; the more qubits, the more capable the quantum computer. Right now the largest quantum computer is 63 qubits from IBM. (Cho)
There are a few key reasons it is difficult: scaling qubits, maintaining coherence, and quantum control. Not unlike operations within a company, quantum systems don’t work the same from small scale to large scale. Currently, quantum computers are being created and tested on a small scale in laboratories. Getting them to the scale needed to solve complex problems requires more than just physics. It requires “time, planning, testing and expertise in a technology which is exceptionally new and untested.” (Cole)
As mentioned above, the way quantum computers work today requires coherence, or for qubits to remain “in sync” over time. Without coherence, qubits cannot maintain their states and are thus error prone. “To build qubits that are perfectly coherent, we would have to control and understand all stray electric and magnetic fields, eliminate all vibrations, even isolate our computer from all light from the ultra-violet down well past the infrared.” (Cho) There are at least six different types of qubits only a few of which are being considered in creating quantum computers. One major type is a superconducting system and its propensity for error can be controlled by keeping the computer in an extremely cold environment. (Greenemeier) However, this just presents another challenge: how to maintain an environment at such an extremely low temperature.
Quantum control is the idea that both hardware and software are maintained overtime to keep the whole system running. Even today there are computers that are responsible for making regular, slight adjustments to hardware and software to keep machines like cars and washing machines. A quantum computer is no different; actually it will require both its hardware and software to maintain extreme precision. (Cole)
Even though quantum computers cannot solve real world problems today, that does not mean progress has not been made. Google claimed to have reached quantum supremacy, or the ability to perform a calculation impossible for a classical computer, in October 2019. IBM actually rebuked Google’s claim, stating that the problem Google’s computer solved was not impossible for a classical computer. It’s interesting to note that in the quantum computing space, even something that seems straightforward, like having reached quantum supremacy, is somewhat subjective.
Both Google and IBM are among the top companies investing in quantum computing. Although public details are scarce, Google seems to be narrowing in on hardware and IBM seems focussed on software and creating a knowledge base. Other large companies investing heavily in the space are Alibaba in information security, connectivity, and computing; Amazon in a quantum computing as a service or a development environment that allows users to explore, design and test quantum algorithms; and Accenture to speed up drug discovery for complex neurological conditions such as multiple sclerosis, Alzheimer’s, Parkinson’s and Lou Gehrig’s Disease. (Srivastava)
Large companies are not the only ones getting in the game. There are startups sprouting up to help develop quantum computing to solve real world problems. For example, Post-Quantum is in the cybersecurity space. Quantum computers are thought to be able to not only break existing security systems, but will therefore be needed to define what new security systems look like. ProteinQure is in the drug development space, specifically the molecular simulation of protein behavior for targeted medical purposes. And, Daimler AG is in the automotive space using quantum computers to improve the life of car batteries.
On the other hand, there are those who do not believe quantum computing will ever beat the hype. Gil Kalai, a mathematician at Hebrew University in Jerusalem, is prominently arguing that quantum computing will never exist in practice. He supports his position from a mathematical and computer scientist background, suggesting the necessary coherence needed to solve complex problems will never exist. “Getting the noise down isn’t just a matter of engineering, he says. Doing so would violate certain fundamental theorems of computation.” (Moskvitch)
That said, many more people, companies, and industries believe strongly that quantum computing will have a significant impact on society, nothing short of the impact the internet had. However, the problems it will likely solve will not be the same problems classical computers solve. For example, quantum computers will likely be great at optimization problems whereas classical computers will continue to be the best solution for email and spreadsheets. It is expected that the two will co-exist; quantum computers will be sustaining.
Below are a few examples of the types of real world problems that quantum computers will likely be great at solving. One example is forecasting weather. Extreme weather events such as hurricanes and tornadoes affect people’s safety, damage to property, and damage to country economies. Even day to day weather forecasting affects from, on the small scale what people wear to, on a larger scale, the farming industry and crop growth. “Weather forecasting requires analyzing huge amounts of data containing several dynamic variables, such as air temperature, pressure, and density that interact in a non-trivial way.” (“Forecasting the Weather Using Quantum Computers”) Quantum computers are likely going to improve tracking and predictions of meteorological conditions by analyzing these huge amounts of data. There is even thinking quantum computers could help minimize climate change. One of the biggest sources of CO2 emissions comes from the chemicals produced in fertilizer. It is thought that quantum computers are not far away from being able to create energy-efficient fertilizers. (Koch)
Cybersecurity is another big field in which quantum computing creates both opportunities and poses risks. Today’s security systems are based on a world of classical computers. Classical computers use two primary classes of algorithms for encryption: symmetric and asymmetric. These types of algorithms take classical computers thousands of years to solve, but, because of their massive computing power, could take quantum computers days or even hours. (Rjaibi et al.) Over the last few years, researchers have been working hard to develop “quantum-safe” encryption. The U.S. National Institute of Standards and Technology (NIST) is already evaluating 69 potential new methods for what it calls “post-quantum cryptography (PQC).” (“What is the Impact of Quantum Computing on Cybersecurity?”) This change will require cybersecurity to be rethought with quantum computers in mind. Although quantum computers are not yet commercially available, IBM and other companies are already working to create more secure measures. (Rjaibi et al.)
Data search is another very interesting field in which quantum computing will likely have a significant impact. Search is everywhere today from consumers’ Google searches to employees’ corporate searches. Being able to increase the speed and accuracy with which information is returned is a highly sought after goal. “A standard search takes a period of time that is roughly proportional to the number of elements in the search.” This is the case because it is possible that the algorithm has to search through all the elements to find the correct one. However, with quantum computing it is thought search can be sped up quadratically such that a search is proportional to the square root of the number of elements. (Emerging Technology from the arXivarchive page)
Technical Progress and Future Prospects
Like most technologies, quantum computers alone do not satisfy most commercial use cases. Solutions are delivered by a variety of components that support the flow of information and value from concept to utility. In order to ascertain the future of this emerging technology it is best to trace the development of this ecosystem as a whole. Outlining this technology ecosystem, its trajectory, and potential future prospects is the focus of this section.
The figure below illustrates the layers of the quantum ecosystem. This pattern follows one that is common in Cloud Computing for classical systems. At the top domain experts (1, 2) engage technology experts to explore a domain space, identify likely use cases, and fund efforts. The inputs (data, instructions) for these use cases are then input into the system through some computer interface (3) that governs the format and composition of valid inputs. These instructions are then transmitted over a network (4) to a datacenter (5). Finally these instructions will interact with a Quantum Algorithm (6) and processed through a control pipeline to the Quantum Computer (7).
The Cloud Computing model has been growing in popularity for compute intensive workloads like Machine Learning and Deep Learning. As traditional computing processors have advanced, and pay-as-you-go business model has emerged as a standard, firms have been quick to take advantage of the low upfront capital expenditure and cost of ownership to experiment. In addition, many engineers have been attracted to cloud platforms.
Look for cloud computing platform heavyweights like Google, AWS, IBM, and Microsoft to capitalize on their advantages and lead the Quantum Computing market. We will explore the implications of this model to chart the future of Quantum Computing over the next 5 year horizon.
Starting at the top of the stack, Domain Expertise is the source of Use Cases and funding. In a “Business Pull” landscape, technology emerges from a need. In the last section, we explored two sample domains that have triggered a business pull effect in Quantum Computing: Cybersecurity and Data Search. However, Domain’s where Quantum Computing theoretically shows promise greatly exceeds these two use cases. In theory Quantum Computing offers improvements to any domain where key challenges are compute intensive. (Atkinson)
Gartner explains that it is the marriage of Domain Expertise and Quantum Expertise that is likely to trigger more business pull, increased interest and investment. (Gartner)
Over the next 5 years, CIOs and Business leaders of Large Organizations across industries (e.g. Fortune 500s) will spearhead efforts to integrate Domain Expertise and Quantum Expertise. This may start off in the form of special working groups. (Gartner) A key constraint is that expertise in Quantum Computing is especially limited. CIOs and Business Leaders looking to start investigating opportunities in this space will face an internal talent shortage. Some firms are taking pains to develop this knowledge area in-house, but more common is the pursuit of external assistance. (Gartner)
A range of boutique agencies have emerged to provide expert advisory services. These firms target Fortune 500 CIOs and Business Leaders. Most efforts are limited duration high-level consulting engagements to explore the disruptive potential of Quantum Computing and educate senior executives.
In the following sections we explore the technical landscape. A firm is looking to run an experiment in Quantum Computing faces the challenge of access to the hardware and software. This is where the existing cloud computing infrastructure providers are vying to add Quantum Computing to their service catalogs.
Interfaces and Operating Systems
Nearly all Fortune 500s have some workloads in the cloud. AWS is the leader but Azure and GCP are also competitive, and IBM offers AI compute services (i.e. IBM Watson). Many firms have arrangements with multiple providers. While it is likely that some firms will pursue on-premises Quantum Computing solutions, it is likely the vast majority of use cases will start in these cloud platforms. As referenced earlier, Cloud Computing platform business model offers synergies with existing services low upfront capital investment.
The first point of contact between the domain/quantum experts and the technology is the computer terminal. This is where technical experts encode instructions (data, procedures) into the system. It may itself have many layers (e.g. operating system, client application, programming language, data format, transport format). This is a mature space for classical computing but will Quantum Computing imply any major changes?
New underlying hardware sometimes sometimes proves incompatible or imperfect for pre-existing abstractions. This interface abstraction layer has yet to see much attention but is nevertheless an interesting one to watch.
Computing Interfaces are developed along a spectrum from tightly coupled to hardware to loosely coupled. Tighter coupling offers the opportunity for greater tailoring to hardware and capture performance advantages. In addition a tightly coupled computer interface offers platform vendors lock-in and network effects. Some traditional computing trends have followed this strategy, for example Apple OSX and Apple Silicon Chips.
Look for platform providers to assert performance trade offs and the emergence of network effects over the coming 5 years (discussed in the next section). In addition, look for movements to emerge promoting more generalizable interfaces that are platform agnostic specializing in quantum computing. Open Source movements have been especially strong in the software development space, especially when sponsored by a consortium of top companies: for example Facebook’s ReactJS project. These formalized movements tend to cement abstractions that are platform agnostic and serve a wide variety of use cases. Platform Providers (Backbone Network and Datacenter)
As discussed in previous sections, Quantum Computing will likely emerge as a service supported on various platform providers leveraging existing Backbone Networks and Datacenters. Data Centers are a key aspect of the delivery of Quantum Computing. They are the physical locations that install, house, and operate the physical computing hardware. Depending on the underlying quantum computing technology, today’s Cloud Platform Providers will need to retrofit existing Data Centers to be further pristine / clean. As discussed in a previous section, Quantum Computing requires control loops that eliminate interference of any kind (seismic, light, electrical). These sorts of interference cause decoherence.
Cloud platforms are investing in developing these capabilities upon which to offer Quantum Computing services. While existing cloud computing platform providers have operational expertise in securing, and maintaining highly available systems at scale, current approaches focus heavily on fault-tolerance, redundancy, and fail-over. In other words these providers specialize in highly available systems, despite error. Quantum Computing potentially requires a different approach. AWS, Microsoft, Alibaba, Google, and IBM have all developed infant Quantum Computing platforms integrated with their cloud computing service offerings. Look for these firms to create “cloud native” offerings, abstracting the quantum computing infrastructure to the Computer Interface layer (e.g. SDKs, CLIs, and integrations with their classical computer products). Look for new approaches to datacenter operation in order to accommodate Quantum Computing as it emerges over the coming 5 years.
Even though the hardware does not exist yet, that hasn’t stopped researchers from developing algorithms in anticipation of those future capabilities. “Algorithms and development environments are proliferating, creating the necessary software underpinnings and staff skills to leverage the hardware as it emerges.” (Gartner) As discussed in a previous section, quantum algorithms take advantage of Quantum Computers by reducing the number of operations needed to reach an outcome. This is measured by the number of operations called quantum gates each applied to a number of qubits.
The study of Quantum Algorithms is advancing quickly. Over three years, from 2016 to 2019, the number of papers on “Quantum Algorithm Zoo” has nearly doubled. Several examples of well-known quantum algorithms include Shor’s algorithm (for factoring) and Grover’s algorithm (for searching).. Grover’s algorithm is expected to be generally operational in the mid-term and to run faster than the best possible classical algorithm for a linear search. This would be an advance that Gartner characterizes as exceptional but not disruptive.
On the longer horizon, Shor’s algorithms are expected to achieve almost exponentially faster performance than classical algorithms for factoring. This achievement will be a disruptive breakthrough because of its implications for cybersecurity among others. For this reason scientists are architecting quantum proof security algorithms before Shor’s algorithm arrives.
Look for Quantum Algorithms to advance in concert with the other aspects of the quantum computing ecosystem, especially when general quantum computing becomes practically available on cloud computing platforms.
Quantum Computers themselves are the last layer of the ecosystem, without these none of the above ecosystem will matter. As one of the previous sections discussed, classical computers work by encoding long strings of bits that can be set to 0 or 1. In contrast, quantum computers employ quantum bits, or qubits, that can be both 0 and 1 at the same time. Current technology uses either ions, photons, or tiny superconducting circuits, to produce these two-way states that give quantum computing its power. This last section highlights the current state of the most promising Quantum Computing technology, its trajectory, and the challenge it needs to overcome.
The leading approach to quantum computing is Trapped Ion technology that uses magnetic fields to suspend charged atomic particles in 3-dimensional space, and then use lasers to coax coupling in-between quantum states and readout results. (University of Oxford Department of Physics) One of the leaders in this field is a startup IonQ, recently announced a milestone featuring 32 qubits IonQ says it has achieved “an expected” quantum volume greater than 4 million. The previous record was by Honeywell, which is pursuing a similar approach leveraging Trapped Ions. (IonQ)
The challenge that Quantum Computing faces is the fragility of quantum systems. As discussed in previous sections, the smallest interference between the suspended ion and its surroundings introduces error. Researchers are working to solve this issue. Solving the error-prone nature of these systems is considered the next “relevant benchmark” for quantum computing. To demonstrate quantum supremacy, Google scientists had to wrangle 53 qubits. To encode the data in a single qubit with sufficient fidelity, they may need to master 1000 of them. (Fortune)
Look for companies like Google, IBM, Alibaba, Honeywell, and IonQ among others to make major investments and likely significant advancements in Quantum Computing in the coming years. When this happens the ecosystem to support it will quickly follow.
Quantum Computing has the potential to change the world. Its ability to make classical factor-based cryptography obsolete, has implications for any organization (or individual for that matter). In addition, a wide variety of industries rely heavily on slow or expensive computation can be disrupted - this includes industries as far afield as logistics and supply-chain management, material science, chemistry, and aerospace design just to name a few.
The lifecycle of an emerging radically innovative technologies technology usually follows a pattern of Technical Progress, Hype and Gloom, and adoption. Based on the promise of the technology and the current state of understanding and interest described above, it is safe to say that we are on the early end of all these curves. That said, due to the possible network effects of cloud computing platforms and synergies with Artificial Intelligence and big data, a revolution in quantum computing capabilities may speed through these curves. Quantum Computing is an emerging technology to watch.
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