© Mark Ollig
AI and quantum computing are converging to create a powerful combination with the potential to dramatically alter how we solve some of our most complex problems.
Quantum computers use quantum mechanics (the physics of behavior at the atomic and subatomic levels) to perform calculations in ways impossible for traditional digital computers.
AI has revolutionized our interactions with technology through natural language processing and machine learning.
Smart devices now understand our spoken commands more accurately, making our interactions intuitive and natural.
AI, including neural networks (computer systems modeled after the human brain), is widely used in healthcare, education, communication, and our electronic smart devices.
When combined with quantum computing’s ability to process vast amounts of information quickly, AI pushes the technological boundaries even further.
Having worked with digital binary telecommunication systems during my telephone career, I was curious about the power of quantum computing.
Quantum computers are built with qubits, which are quantum bits capable of existing in a superposition of states, meaning they can represent multiple values simultaneously.
These qubits can also become entangled, meaning they become linked so strongly that what happens to one immediately affects the other, no matter how far apart they are.
The unique ability of qubits to exist in multiple states at once (like a coin having both heads and tails) allows them to explore many possibilities simultaneously.
In contrast, traditional digital computers operate on binary bits, either 0 (off) or 1 (on), representing high and low voltage states of electrical circuits.
Digital computers use binary representation and Boolean operations (AND, OR, NOT) to perform basic arithmetic functions.
Quantum computers harness the unique behaviors of the quantum world, allowing for unique calculations.
Their performance depends not only on qubit count but also on the design of quantum logic gates (instructions) and selected problem-solving algorithms, such as Shor’s (for factoring large numbers) and Grover’s (for searching databases).
Quantum gates manipulate qubits to perform calculations and are like mathematical formulas, and frameworks like IBM’s Qiskit allow for programming quantum computers using languages like Python.
Hadamard or CNOT quantum gates manipulate the states of qubits within a series of quantum algorithms to solve problems.
For example, quantum gates like Hadamard can put a single qubit in a state where it’s both 0 and 1 simultaneously, while CNOT gates can control two qubits together, acting like a switch where the state of the first qubit affects the second.
Quantum computers have the potential to explore numerous solutions simultaneously for certain types of problems by leveraging superposition, where qubits can exist in multiple states at once.
Superposition delivers a speed advantage over traditional digital computers, which must test solutions sequentially in a logical sequence.
This potential can be realized by developing proficient quantum algorithms and overcoming technological limitations.
Imagine a conventional binary bit coin with two distinct sides – heads and tails. It can only represent one of two values at a time: heads could represent 1, and tails could represent 0.
Now, imagine a qubit coin that spins incredibly fast and appears as a blur of both heads and tails.
This blur represents the qubit existing in a superposition of both states; it’s not just that you don’t know the outcome (whether it’s heads or tails); it truly hasn’t settled into one state or the other (it exists as both simultaneously).
Only when you stop the coin (similar to making a quantum mechanics measurement) does it collapse into a definite state of either heads or tails.
Entanglement is an even stranger phenomenon.
Two linked quantum particles become so connected that their states are intertwined – what happens to one particle immediately determines what happens to the other, regardless of the physical distance between them.
This quantum entanglement connection defies our everyday understanding of how objects interact.
Scientists primarily work with two types of qubits in quantum computers: superconducting and trapped ions.
Superconducting qubits are faster but require extremely low temperatures (around -454°F, close to absolute zero, which is -459.67 degrees Fahrenheit, while trapped ion qubits can store information more reliably but also require frigid temperatures (around -436°F).
Quantum computers require these frigid temperatures to minimize the disruptive effects of thermal electronic “noise” on delicate quantum states like superposition and entanglement.
This noise can cause qubits to lose their quantum properties (decoherence), delaying calculations.
Extreme cold is essential for quantum computers. It minimizes the vibrations of atoms, reducing thermal noise and allowing for longer, more reliable quantum operations and accurate results.
Superconducting qubits rely on the phenomenon of superconductivity, which only occurs at temperatures near absolute zero.
The future may see a “quantum internet,” enabled by a sophisticated AI-quantum architecture under development by organizations such as the Quantum Internet Alliance (QIA) and the Quantum Internet Task Force (QITF).
Combining AI’s analytical power and quantum computing’s processing platforms will lead to future discoveries and advancements far beyond what we can imagine today.
Mr. Spock from “Star Trek” would undoubtedly find it all “fascinating.”
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| IBM’s Heron is a 133-qubit quantum processor that uses techniques designed to reduce thermal noise errors and reliably manage up to 1800 gates within the stability times of its qubits. Heron will be used with the new IBM Quantum System Two computer. |
