A Cat, A Bit and a Qubit - The Key Differences Between Classical and Quantum Computing

By Ravi Ravoory & Mark Gilmor

This post describes the fundamental differences between classical and quantum computing. It covers the basic units of information, principles of operation, computational power, error rates, inter-connectivity, & scalability.  These differences illustrate the important potential and limitations of quantum computing compared to classical computing. The cat below will make sense as you read on. 

Basic Units of Information

Classical computing uses bits as its fundamental unit of information. A bit can be in one of two states: 0 or 1. This binary system creates all classical computing processes.

Quantum computing utilizes qubits (quantum bits). A qubit can exist in a superposition of states, representing both 0 and 1 simultaneously. This capability is derived from the principles of quantum mechanics. 

Principles of Operation

Superposition

A classical bit or an object is at one place at any given time. As an example a person can either be watching TV at home or relaxing on a beach. It is not possible to be at both locations at the same time.

A qubit also called a subatomic particle can exist in a superposition of states, it can theoretically exist in multiple places at once before being observed. A single subatomic particle can exist in point A and point B at the same time until we observe it. And at that point, it only exists at either point A or point B. This peculiar feature allows quantum computers to process many possibilities simultaneously.

This is best understood through the experiment of Schrödinger's cat, a famous thought experiment in quantum mechanics devised by Austrian physicist Erwin Schrödinger in 1935.

Schrödinger's cat thought experiment highlights the peculiar and counterintuitive nature of quantum mechanics, specifically the idea that particles can exist in multiple states at once (superposition) and that the act of observation affects the outcome. If you aren't familiar with this thought experiment it is worth investigating.

Entanglement

A classical bit operates independently. The table below represents the relationship between a classical bit and a Qubit in an entangled state.

A qubit can become entangled, creating a correlation between their states regardless of distance. Entanglement is a key resource for quantum computing. If we know something about the probabilistic positioning of one qubit, then we know something about the probabilistic positioning of another qubit. This means that these qubits can actually work together to create a complex and powerful ecosystem. Suffice to say, when qubits get past 100 the classical bit count literally becomes astronomical. As of 2024 we are at 1,300 atomic qubits. 

Interference

A classical bit lacks a mechanism similar to quantum interference. In other words it is not really 'interesting'.

Interference is what happens when a stone is thrown in a pond. The waves created by the stone  spread and travel across the pond. Eventually they meet  and interact. This interaction is called interference. A qubit interacts with another qubit to create  interference which enables it to amplify correct solutions and diminish incorrect ones, enhancing the likelihood of arriving at the correct result.

Computational Power and Speed

Classical computers follow predetermined paths to solve problems. Their performance improves linearly with added processing power and parallelism techniques.

Quantum computers can solve certain problems exponentially faster than classical computers. For instance, Shor's algorithm enables efficient factoring of large numbers, and Grover's algorithm provides quadratic speedup for unstructured search problems. This is possible due to the use of its superposition, entanglement and interference properties.

Error Rates and Correction

Classical computers have low error rates and benefit from well-established error correction methods.

Quantum computers are more susceptible to errors due to decoherence and noise caused by the inherent properties of qubits. Quantum error correction is complex and remains an active area of research, but progress is being made toward practical solutions.

Algorithms and Applications

Classical algorithms are efficient for a wide range of tasks, particularly those involving sequential and straightforward problem-solving processes.

Quantum algorithms excel in specific areas such as:

- Factoring large integers (e.g., Shor's algorithm)

- Quantum simulations (e.g., simulating molecular structures)

- Optimization problems (e.g., quantum annealing)

- Database search (e.g., Grover's algorithm)

Physical Implementation

Classical computers are built using silicon-based transistors and electronic circuits. The technology is mature and well-understood.

Quantum computers are implemented using various technologies, including:

- Superconducting circuits

- Trapped ions

- Photonic systems

- Topological qubits

Each implementation has unique challenges and advantages.

Development Stage

Classical computing is a mature technology with extensive infrastructure and applications across all sectors.

Quantum computing is in the developmental stage. Although significant progress is being made, practical, large-scale quantum computers are not yet available.

The combination of quantum computing and the rapid development of AI applications will create a much more powerful symbiotic relationship.

With a sufficiently powerful quantum computer existing AI large language models can be trained significantly faster resulting in faster inference and more efficient processing including quantum machine learning.

Existing quantum optimization algorithms can benefit AI  applications like route planning, annealing etc.

Quantum computers will enable Gen AI also called quantum enhanced AI will enable more accurate and faster drug modeling, systems modeling, climate modeling etc.

The Convergence: Bits / AI Neurons / Qubits

Parallelism

Classical computing achieves parallelism through multi-core processors and parallel processing techniques. This is similar to several workers each handling a different task at the same time. 

Quantum computing's parallelism is inherent due to superposition, allowing simultaneous processing of multiple possibilities, which is fundamentally different from classical parallelism. This is like having a single worker who can simultaneously handle multiple tasks at once due to some special ability. 

Classical and quantum computing represent two distinct paradigms, each with its own unique strengths and challenges. Classical computing remains the foundation of today's technology, while quantum computing promises to revolutionize specific fields by tackling problems currently intractable for classical computers. The introduction of AI further amplifies both the opportunities and threats presented by these technologies. This convergence is undeniable and understanding these key differences is crucial for fully leveraging the potential of both classical and quantum computing.

Understanding these key differences and the interplay between classical computing, quantum computing, and AI is crucial for fully leveraging the potential of these technologies. Recognizing the specific strengths and applications of each paradigm, businesses and researchers can make informed decisions about where to invest their resources and how to best integrate these advanced technologies into their operations.