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A disruptive innovation that presents both opportunities and dangers
A disruptive innovation that presents both opportunities and dangers
The advent of mature quantum information technologies holds the potential for significant disruption across numerous fields (Barker, Polk and Souppaya, 2021). A critical concern is that, theoretically, a fully developed quantum computer could readily break certain widely used encryption methods. However, the ongoing advancements in quantum computing research are spurring innovation in cryptography, especially the creation of algorithms designed to withstand attacks from quantum computers. Moreover, research into quantum technologies is opening doors to novel cryptographic approaches rooted in the principles of quantum physics ("quantum cryptography" and "quantum key distribution") rather than traditional mathematics. In essence, quantum information technologies not only challenge existing cryptosystems but also drive the development of solutions to these challenges ("quantum-resistant cryptography") and explore the cryptographic opportunities presented by quantum computing itself.
What is quantum computing?
What is quantum computing?
Quantum technologies operate on the principles of quantum mechanics, the branch of physics governing the behavior of minuscule particles. Among these technologies is quantum computing, a novel computing paradigm (Grumbling and Horowitz, 2019). Quantum computing, and more broadly quantum information technologies, aim to harness the properties of nature at the atomic level to achieve tasks beyond the capabilities of current technologies (US Government Accountability Office, 2021). Initially conceived in 1982 by Nobel laureate Richard Feynman as a tool for simulating quantum systems, quantum computing has evolved into an established interdisciplinary field spanning physics, computer science, and engineering, involving universities, research centers, and companies globally (BSI, 2021).
Traditional computers rely on bits, intangible binary digits representing the state of a tangible transistor, akin to a tiny on-off switch. Information is thus binary: each transistor is either a 0 or a 1. In contrast, quantum computers encode information in qubits. A qubit represents a property called "spin," the intrinsic angular momentum of an electron, resembling a tiny compass needle pointing up or down. By manipulating this "needle" to encode information into electrons, researchers can exploit the ability of quantum systems to exist in multiple states simultaneously (superposition). This allows a qubit to represent 0, 1, or a combination of both at the same time (Nellis, 2022). Quantum computers leverage superposition to exponentially increase processing power. They also utilize the intrinsic linking of qubits (entanglement), where acting upon one qubit, such as through measurement, can reveal information about other linked qubits regardless of distance. Entanglement enables quantum computers to perform parallel computations on entangled qubits (US Government Accountability Office, 2021).
Quantum computers are projected to exhibit a massive leap in both processing power and speed. A traditional computer with N bits can represent 2N states. For example, a 1-bit computer represents 21 (2) states (0 or 1), a 2-bit computer represents 22 (4) states (00, 11, 01, 10), and so on. A quantum computer with N qubits, however, can represent 2N quantum states simultaneously. While the number of possible states in a traditional computer doubles with each added bit, scaling linearly with the number of bits, the number of possible states in a quantum computer increases exponentially with each additional qubit (Congressional Research Service, 2022). Consequently, in theory, quantum computers' processing power could surpass that of traditional computers by many orders of magnitude, enabling the much faster solution of certain problems, even those intractable for traditional computers within a reasonable timeframe. This is known as "quantum supremacy" or "quantum advantage" (Preskill, 2012). To illustrate this difference, modeling a 54-qubit quantum computer would require approximately 254 bits (around 18 quadrillion bits) of traditional memory. As of 2019, only one traditional supercomputer globally, the IBM Summit, possessed such capacity. Modeling a 72-qubit quantum computer would require 272 bits, necessitating the equivalent of stacking 262,000 Summit-type supercomputers! Modeling a 100-qubit quantum computer would demand more bits than there are atoms on our planet, and a 280-qubit computer would require more bits than there are atoms in the known universe (Sedik, Malaika and Gorban, 2021).
Leveraging unique quantum properties, entirely new quantum algorithms can significantly accelerate specific computational tasks. For instance, the most well-known quantum algorithms, Grover's and Shor's, offer polynomial and exponential speedups, respectively. A polynomial speedup means a quantum computer solves a problem in time T (e.g., 1,000 steps) while a traditional computer requires T2 (e.g., 1,000,000 steps). An exponential speedup is even more dramatic: a quantum computer might take time T (e.g., 100), whereas a traditional computer would take 2T (e.g., 2100), a number with 31 digits (Sedik, Malaika and Gorban, 2021).
However, these figures remain purely theoretical because constructing a quantum computer with sufficient processing power for practical applications is immensely complex. Consequently, despite enthusiastic announcements and optimistic predictions from some stakeholders, few independent experts are willing to even estimate a timeline for the maturity of quantum computing. The design and engineering challenges constitute a significant portion of this complexity. For example, researchers and engineers must devise methods to completely isolate a quantum computer from its surrounding environment to protect the delicate state of the qubits, while simultaneously enabling controlled interactions with them (Institute for Quantum Computing, n.d.; BSI, 2021). The loss of information due to environmental noise, known as quantum decoherence, increases with the number of qubits and necessitates maintaining current quantum computers at temperatures near absolute zero (−273.15 °C, −459.67 °F). Quantum error correction techniques can be implemented to mitigate decoherence, but these require additional qubits. Therefore, public announcements of significant progress in quantum computing engineering based solely on an out-of-context number of qubits should be viewed with caution. While it is an active research area, no one can confidently predict how long it will take researchers to master error correction (Cho, 2020).
Beyond hardware and engineering hurdles, entirely new algorithm design principles that exploit quantum features will need to be invented, along with a completely new software stack (Grumbling and Horowitz, 2019). Designing quantum algorithms is considerably more challenging than designing algorithms for traditional computers. According to some experts, as of 2019, only a few dozen quantum algorithms had been developed (Vardi, 2019). Mature quantum computers are not expected to replace today's computers or smartphones but are more likely to function as specialized super-calculators capable of handling certain problems or algorithms more efficiently than traditional computers (SQT, 2021).
According to a 2019 "consensus study report" by the US National Academies of Sciences, Engineering, and Medicine, "the progress required to bridge the current [technological] gap makes it impossible to project the timeframe for a large error-corrected quantum computer, and while significant progress in these areas continues, there is no guarantee that all these challenges will be overcome. The process of bridging this gap might expose unanticipated challenges, require techniques that are not yet invented, or shift owing to new results of foundational scientific research that change our understanding of the quantum world" (Grumbling and Horowitz, 2019). In fact, some researchers have even expressed skepticism about the feasibility of ever building a mature quantum computer capable of achieving practical tasks (Kalai, 2011; Dyakonov, 2018).
In their 2017, 2019, and 2020 assessments, the German Federal Office for Information Security (BSI) examined the progress of quantum computer development and its implications for digital security. The BSI noted that the point at which current traditional supercomputers could no longer simulate quantum computers was reached in 2019, although design limitations prevented this from affecting the robustness of current cryptography. Quantum processors still lack the scale needed by several orders of magnitude to mount effective cryptographic attacks. The BSI stated that scaling up quantum computing technologies to a cryptographically relevant level would require an enormous undertaking, potentially involving infrastructure the size of a football field and a coordinated research program pooling major research and development resources from industrialized nations, akin to the Apollo and Manhattan projects. However, recent progress has accelerated due to the involvement of significant industrial players and large research programs, and commercial applications could further accelerate this progress. Consequently, estimating a realistic timeframe for cryptographically relevant quantum computers remains challenging (BSI, 2021).
Quantum communication, another potentially disruptive quantum information technology under investigation, utilizes the laws of quantum physics to transmit information via quantum particles, such as single photons of light through optical fiber or free space (Kristjánsson, Gardner and Chiri, 2021). Superposition can be used to allow quantum particles to travel along multiple communication lines simultaneously, making the information more resilient to transmission errors. Entanglement enables the transfer of quantum information over long distances, where the sender and receiver each hold half of the entangled photons. Quantum information is transferred through a combination of entanglement and traditional communication, with information encoded in controllable parameters of the photons, such as their polarization. Controlling the properties of individual photons requires specialized generation and detection devices operating under specific engineering conditions, such as cryogenic temperatures (below -153°C, -243°F). Notably, quantum computing, albeit at a basic level, is necessary for quantum communication (OFCOM, 2021).
Quantum communication could lead to a significant advancement in cryptography through the development of quantum key distribution (discussed further below). It also promises ultra-secure communication because the fragile state of qubits in transit would ensure the confidentiality of the communication. If an eavesdropper attempts to observe a qubit, its quantum state would immediately "collapse" to either 0 or 1, leaving a detectable trace of the observation (Giles, 2019). Theoretically, quantum communication could also enable the development of a quantum Internet, linking quantum computers to pool their capabilities. However, the very concept of a quantum Internet is still debated (BSI, 2021). The Quantum Internet Research Group of the Internet Research Task Force is exploring the design and construction of quantum networks (IRTF QIRG, n.d.).
Nevertheless, the race to develop quantum computing has begun. The substantial potential benefits of quantum information technologies in fields like materials science, pharmaceuticals, energy, and finance (US White House, 2022) are attracting significant attention and investment from both public and private stakeholders. According to McKinsey, private investors invested USD 2.35 billion in quantum technology start-ups in 2022 (2023). Furthermore, many OECD governments are adopting national quantum strategies and allocating considerable research budgets.
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