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Quantum Information Technology
A guide to quantum information technology and its applications
What is quantum information technology?
Quantum information technology (QIT) is a rapidly advancing field that leverages quantum mechanics to manipulate information in novel ways, leading to vast improvements over classical technologies. QIT exploits quantum phenomena like superposition and quantum entanglement to overcome the challenges of information storage, processing, transmission, and security. The field of QIT encompasses a spectrum of applications that leverage quantum systems, including quantum computing, quantum sensing, and quantum communications.
We are on the brink of an information technology (IT) revolution enabled by quantum mechanics. Achieving it will require collaborative research to address the challenges inherent in trying to control the properties of the quantum realm. Every breakthrough deepens the understanding of quantum properties and leads to new architectures and innovations that bring us closer to achieving quantum supremacy and commercially viable applications.
QIT essentials
Quantum: Discover the possibilities
Tap resources to help you understand quantum mechanics and the technologies it powers.
Quantum fundamentals
Understand basic quantum concepts and what is necessary to realize its full potential.
Quantum sensing
Learn about quantum sensing theory, applications, and enabling technologies in this course.
How to build a superconducting quantum processor
Explore the core concepts and components needed to build a superconducting quantum processor.
Timeline of key developments in quantum
Today’s quantum technology breakthroughs owe a great deal to algorithmic and theoretical pioneers. To grasp the significance of quantum technology, you must understand how we arrived at this point.
Early 20th century: Pioneering research in quantum mechanics
1900: Max Planck’s quantum hypothesis introduces the concept of quantization to explain blackbody radiation.
1905: Albert Einstein publishes his theory of the photoelectric effect, which suggests that light comprises discrete packets of energy called photons.
1924 – 27: Louis de Broglie proposes the wave-particle duality of matter, prompting Erwin Schrödinger’s wave mechanics research, Werner Heisenberg’s matric mechanics, and Max Born’s probabilistic interpretation of quantum mechanics.
Mid-20th century: Advancing foundational QIT discoveries
1932: James Chadwick’s discovery of the neutron prompts the development of atomic nuclei-related quantum theories.
1935: Einstein, Boris Podolsky, and Nathan Rosen publish “Can Quantum-Mechanical Description of Physical Reality Be Considered Complete?” Better known as EPR, the paper questions the completeness of quantum mechanics.
1947: Willis Lamb and Robert Retherford discover the Lamb shift, validating quantum electrodynamics, which paves the way for quantum field theory.
1959: Richard Feynman proposes the concept of the quantum computer.
1968: Paul Dirac introduces quantum gates, laying the foundation for quantum computation.
1970s: Quantum information theory, including quantum cryptography and quantum teleportation, gains popularity.
Late 20th century: Forging new paths in QIT applications
1981: Feynman proposes quantum system simulation using quantum computers.
1984: David Deutsch proposes the concept of a universal quantum computer in his paper, “Quantum Theory as a Universal Physical Theory.”
1994: Peter Shor’s eponymous algorithm for finding prime factors of an integer demonstrates quantum computing’s impact on cryptography.
1998: Isaac Chuang demonstrates the first quantum gate using nuclear magnetic resonance.
21st century: Pushing the boundaries of quantum technology
Early 2000s: The first commercial demonstrations of quantum key distribution systems for secure communication implementations occur.
2009: Scientists demonstrate a solid-state quantum processor using superconducting qubits for the first time.
2010s: Discoveries in trapped ions, growing qubit registers, and error correction protocols accelerate progress in experimental quantum computing.
2020s: Increasing government, academic, and industry investment advance breakthroughs in quantum communication, sensing, metrology, and simulation.
The fundamentals of quantum mechanics
Believing that the natural laws governing the universe are determinable, Einstein said of quantum mechanics, “God tirelessly plays dice under laws which he has himself prescribed.” The idea that the state of the universe at a point in time can determine its state at all other times is a core tenet of classical mechanics and, indeed, science.
Quantum research in the early 20th century revealed an aberrant realm where systems deviate from the strict rules of classical mechanics, electricity and magnetism, and general and special relativity.
What are the key distinctions between classical and quantum mechanics?
The Heisenberg uncertainty principle (HUP) represents a shift from classical predictability to quantum probability and highlights the differences between classical and quantum mechanics. HUP asserts that the more precisely we know one property of a particle, the less precisely we can determine other properties.
For example, the more precisely you measure location, the greater the uncertainty you would have in the speed, and vice versa. This is because in order to see the particle, you must shine light on it; to measure its location, the light must possess short wavelengths. However, because these short-wavelength light sources are energy-dense, they disturb the particle’s speed. Therefore, the act of trying to accurately measure where a particle is makes it difficult to measure its speed with any precision.
HUP serves as a gateway to understanding the profound differences between classical and quantum mechanics, including superposition, qubits, and entanglement.
Key quantum mechanics concepts to understand
A common mathematical description of qubits uses the Bloch Sphere. Imagine a sphere in a cartesian plane centered on (0,0,0) with radius of 1. We call the point at the north pole state |1> and the point south pole state |0>, and these end up being out basis states; they become the basis of all other points on the sphere. If we then imagine all the possible state a qubit can be as lying on the surface of the sphere, we can write each possible state as some linear combination of |0> and |1>. This shows us that the qubit can take on infinitely many states, as there are infinitely many points on the surface of the sphere, and that each state is a combination (or superposition!) of the 2 basis states.
A probability amplitude is a complex number used to describe how systems behave in quantum mechanics. Probability amplitudes are one form of a probability wave describing the odds of finding a particle in given locations. They connect the system’s quantum state vector and the observational results of that system.
Quantum technology is highly susceptible to errors caused by noise, hardware imperfections, and environmental factors. Error correction techniques that detect and correct errors in quantum states are critical for developing fault-tolerant, commercially viable quantum systems. Developing efficient error correction codes and protocols that can protect quantum information against noise and decoherence while minimizing resource costs is a priority challenge for researchers.
Core components of quantum information technology
Qubits
Quantum bits, or qubits, are the building blocks of QIT. They are the most fundamental units of quantum information. Classical data bits exist in two states, written as 0 and 1. While they can take many forms and perform a vast array of functions, a bit must always be in either a 0 state or a 1 state.
If you picture a sphere, the surface represents all of the possible states of a qubit. Classical bits are like points located only at the poles of the sphere, fixed in either the 0 or 1 state. Qubits can occupy any point along the sphere’s surface, representing an infinite number of possible states. This freedom allows qubits to encode and process exponentially more information than classical bits do.
Qubits do this through superposition and entanglement. Superposition supplies their remarkable flexibility and power. Entanglement enables qubits to become correlated in such a way that the state of one qubit instantly influences another, regardless of the distance between them. These unique properties shatter the constraints of classical bits and allow qubits to exist in a rich, complex state space. They can encode and process quantum information in ways that promise meaningful advancements in computation, communication, and cryptography.
Superposition
Going back to the sphere analogy, superposition lets qubits carry information between the 0 and 1 states at the same time. In classical physics, objects have definitive properties at any given time. In quantum physics, however, particles like electrons, photons, and atoms can exist in a combination of states simultaneously, known as superposition.
Schrödinger’s cat is a well-known thought experiment that describes how the quantum superposition of non-decayed and decayed radioactive nuclei can influence superposition on a macroscopic level. In this gruesome scenario, a scientist places a cat in a box with a radioactive mechanism that controls a vial of poison. The moment of the poison’s release is unknown; thus, the cat occupies a state of both life and death until we open the box and observe its fate.
Quantum mechanics cannot predict the fate of Schrodinger’s cat. Instead, it provides us with the probability of which state we will find the cat in when we open the box across a large set of identical experiments.
Superposition is what enables quantum bits (qubits) to perform highly complex functions by representing multiple states simultaneously. Going back to the sphere analogy, superposition states have amplitudes and enable qubits to carry information between the 0 and 1 states at the same time. As the number of qubits increases, the number of available probability amplitudes increases exponentially. It is this property that gives quantum technology the probability to dramatically accelerate the speed of computational tasks relative to their classical counterparts.
Quantum entanglement
Entanglement is the key to harnessing quantum information processing. Quantum entanglement occurs when the states of two or more particles become correlated such that the state of one particle instantaneously influences the state of another, irrespective of the distance between them.
This correlation persists when the entangled particles separate, even by long distances. Without entanglement, each qubit exists independently on the sphere, in its own world with its own possible states. When qubits become entangled, however, their positions become intricately linked, enabling them to explore a broader range of states than they could individually.
The coordinate movements of entangled qubits on the surface of the sphere maximize the flexibility enabled by superposition. If you perform a measurement on one entangled qubit and collapse it to a specific state, the state of the other qubit is determined instantaneously as well, regardless of where on the sphere it resides. Entanglement enables qubits to leverage their collective quantum nature to unlock the potential for highly efficient computation, secure communication, and novel cryptographic protocols.
This graph depicts the two observers, Alice and Bob, sharing an entangled state.
Quantum decoherence
While the previously explained properties enable qubits to hold much more computational power than classical bits, a big challenge for quantum computers is a phenomenon called quantum decoherence.
Quantum decoherence occurs when a system interacts with elements in the environment, such as air, thermal radiation, or a non-demolition measurement apparatus. To understand decoherence, you must first understand quantum coherence. In its simplest form, coherence refers to the measure of the relationship between different possible states within the quantum system. This information is necessary for the quantum computer to function. Isolation maintains coherence.
Quantum decoherence occurs when the system interacts with its internal and external environment. When this happens, the system’s information and the environmental information comingle, making it difficult to distinguish quantum system signals from environmental noise. Qubit states are unstable, and different environmental factors can affect the state of a qubit in an unknown way, similar to noise in scientific measurements. A stray photon or a fluctuation in temperature can cause an energy shift in the qubit. As a result, the state moves closer to collapse.
Quantum interference
In addition to the influence of environmental factors, qubits in an entangled system can affect the state of other qubits. Quantum interference occurs when the probability amplitudes of different states a qubit can take interfere with each other, causing either constructive or destructive interference effects. Each trajectory corresponds to a different sequence of operations applied to the qubit.
Constructive interference occurs when the probability amplitudes of trajectories align and reinforce each other, increasing the likelihood of finding a qubit in certain states. Destructive interference occurs when the trajectories’ probability amplitudes cancel each other out, reducing the probability of finding the qubit in certain states.
Quantum interference plays a crucial role in quantum information processing. By manipulating the quantum states of qubits and controlling the interference effects, quantum algorithms can exploit interference to enhance computational efficiency and solve problems considered intractable for classical systems.
Quantum error correction
In order to combat quantum decoherence and noise in the system, quantum computers use entanglement and interference to help correct errors. Classical error correction is easier to work with. A bit can be only 0 or 1, and an error can only be a bit flip. To combat this, classical computers encode their bits redundantly. Instead of using 1 bit to represent 0 or 1, they use multiple, such as 000 or 111. An error might look like 010, where we can assume that this means 0, and the middle bit just had an error. This also works because bit flips in classical bits are rare.
Qubits are different. While their state can deviate from expectations, we are unable to observe the shift because of the measurement collapse that would result from observations. The way we work with this is similar to classical bits in that we encode the qubits redundantly but put them in an entangled state with other ancillary qubits. In the entangled state, each qubit’s state connects to the other qubits’ states. This way, we can extract information from an ancillary qubit and infer the state shift in the computational qubit and thus correct it.
Quantum information processing and communication
The properties of quantum mechanics underpin the reasons QIT promises revolutionary potential for IT. The processing power of a quantum system expands exponentially with each additional qubit. Arranging the interference between the amplitudes of a multi-qubit processor in various ways unlocks solutions to computational tasks that are impossible for even the most powerful classical supercomputer to achieve.
In classical physics, we observe systems passively. We can, for example, watch a person kick a ball without detection or influencing the action. Such is not the case for quantum. It is impossible to observe quantum information without interfering or leaving behind evidence.
Moreover, entangled qubits can exist in states that cannot be factored in. The majority of quantum states involve entanglement, thus phenomenon is critical for quantum processing. Because entangled qubits do not need to be in the same location, entanglement opens up a host of communication technology opportunities.
These and other examples demonstrate quantum’s immense potential for computer processing, cryptography, secure communication, and more.
Types of quantum information technology
Quantum computing
Quantum computers represent a groundbreaking paradigm in computation, harnessing the principles of quantum mechanics to perform calculations at unparalleled speeds. Central to their operation are qubits, the quantum counterparts to classical bits, which exploit the phenomena of superposition and entanglement to encode and process information in fundamentally different ways.
Superposition enables qubits to exist in multiple states at one time, offering the potential for exponential parallelism in computation. Meanwhile, entanglement establishes correlations between qubits that defy classical intuition, enabling the creation of highly correlated states that encode and manipulate quantum information with extraordinary efficiency.
Through the phenomenon of interference, where the probability amplitudes of different quantum states interfere with one another, quantum computers can exploit the computational advantages of superposition and entanglement to perform complex computations. This method leads to potential speedups for specific computational tasks, such as integer factorization with Shor’s algorithm and unstructured search with Grover’s algorithm.
Quantum computers hold immense promise for artificial intelligence, cryptography, materials science, optimization, and other fields. However, realizing this potential requires overcoming significant challenges, such as decoherence, noise, and the engineering of scalable quantum hardware.
Despite these hurdles, ongoing research and development efforts are advancing the capabilities of quantum computing systems. As progress continues, we anticipate the emergence of increasingly powerful and versatile quantum computers that push the boundaries of what is computationally achievable, revolutionizing the computing landscape as we know it.
Quantum sensing
Quantum sensing is a cutting-edge technology that uses the principles of quantum mechanics to achieve ultra-high-precision measurements beyond the capabilities of classical sensors. At its core, quantum sensing exploits quantum properties such as superposition and entanglement to enhance measurement sensitivity and accuracy.
Highly precise atomic clocks are a prominent example of quantum sensing. Atomic clocks rely on the quantum properties of atoms, typically cesium or rubidium, to measure time with extraordinary accuracy. By leveraging the precise frequency of atomic transitions, atomic clocks maintain timekeeping accuracy at the level of nanoseconds over periods of millions of years.
Another key application of quantum sensing is quantum magnetometry, which aims to detect and measure magnetic fields with unprecedented sensitivity. Quantum magnetometers use the quantum properties of atomic spins to sense minute changes in magnetic fields. Quantum magnetometry has applications in various fields, including geophysics, navigation, and medical imaging, where high-precision magnetic field measurements are crucial.
Additionally, quantum sensors are under development for other applications, such as gravity sensing, inertial sensing, and quantum imaging. Quantum gravity sensors, for example, aim to detect tiny variations in gravitational fields, offering insights into geological structures, underground resources, and environmental changes. Inertial sensors based on quantum technology could revolutionize navigation systems by providing precise positioning and orientation information in GPS-denied environments.
Advancements in quantum technologies, including qubit control, quantum measurement techniques, and quantum error correction, are driving the development of quantum sensors. These developments enable the creation of sensors with unprecedented sensitivity, precision, and robustness, opening up new opportunities for scientific research, industrial applications, and technological innovation.
Overall, quantum sensing holds the promise of transforming fields such as geophysics, navigation, medical diagnostics, and environmental monitoring by providing ultra-high-precision measurements unattainable with classical sensors. As research and development into quantum sensing advances, we can expect to see even greater strides in precision measurement technology, leading to new insights and discoveries across various domains.
Quantum communication
Quantum communication is an emerging field that uses quantum mechanics principles to secure the transmission of information between parties. Unlike classical communication protocols, which rely on mathematical algorithms for encryption, quantum communication protocols leverage the inherent properties of quantum systems to achieve unbreakable security.
At the heart of quantum communication lies the phenomenon of quantum entanglement. In this concept, the states of two or more particles become correlated so that the state of one particle immediately influences the state of another, regardless of how far apart they are.
A leading quantum communication application is quantum key distribution (QKD), which enables the generation of cryptographic keys with unconditional security. In a typical QKD protocol, two parties, often referred to as Alice and Bob, exchange quantum states encoded with random information. Any attempt to intercept or measure these quantum states would disturb them, revealing the presence of the eavesdropper, often called Eve, to Alice and Bob.
The laws of quantum mechanics, specifically the no-cloning theorem and the principle of quantum indeterminacy, guarantee QKD protocol security. These principles ensure that any attempt to measure or copy the quantum states without detection results in irreversible disturbance, thereby preventing eavesdropping without detection.
Beyond QKD, quantum communication encompasses other cryptographic protocols, such as quantum teleportation, quantum digital signatures, and quantum coin flipping. These protocols leverage the unique properties of quantum systems, including superposition and entanglement, to enable secure communication and authentication between parties.
Quantum communication technologies are still in the early stages of development, but they hold immense promise for applications requiring secure and private communication, such as banking, government communications, and military operations. As research and development into quantum communication advances, expect to see increasingly sophisticated and practical implementations of quantum communication protocols, ushering in a new era of secure communication in the digital age.
Quantum computing architectures
Superconducting qubits
Superconducting circuits serve as qubits to encode and manipulate various states.
Advantages: Scalable, enable fast gate operations, and compatible with existing semiconductor technology
Challenges: Coherence times, gate fidelity, and inter-qubit connectivity
Trapped ion qubits
Electromagnetic fields trap and manipulate individual ions to encode qubits.
Advantages: Longer coherence times, high gate fidelities, and potential for fault-tolerant quantum computation
Disadvantages: Scalability, precise control over individual ions, and complex experimental setups
Topological qubits
Unlike other qubits, which exploit the individual properties of atoms, topological qubits store information in the topological properties of a physical system. Researchers use topological quantum states of matter to encode qubits, providing inherent error protection.
Advantages: Long coherence times, protection against external disturbance, scalable, and robustness against errors
Disadvantages: No working prototypes and difficulty reaching all points on the Bloch sphere
Advantages of QIT for industry
Quantum cryptography represents a paradigm shift in communication security and enables better ways to protect sensitive data from being intercepted and decrypted by bad actors.
Quantum computers enable precise molecular interaction simulations that will accelerate the discovery of new pharmaceuticals and materials with desired properties.
Quantum algorithms have the potential to solve for complex optimization challenges more efficiently, resulting in better portfolio management, supply chain optimization, and logistics planning.
Quantum machine learning algorithms accelerate training of deep learning models and improved pattern recognition, leading to significant advancements in artificial intelligence (AI).
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