Quantum Computing: The New Paradigm
A quantum computer is a computing device that uses quantum bits (qubits), which can exist in multiple states simultaneously due to superposition and be correlated through entanglement, enabling it to solve certain complex problems much faster than classical computers.
The journey to quantum computing began with the early developments in quantum mechanics. Max Planck's pioneering work revealed the concept of discreteness at sub-atomic levels. J.J. Thomson's discovery of electrons in the cathode ray tube, followed by Rutherford's description of electrons orbiting the nucleus, laid crucial foundations. An unexpected source of insight came from a bad cigar, which played a role in uncovering the concept of spin as intrinsic angular momentum in electrons (Friedrich & Herschbach, 2003).
Quantum physics aims to explain the behavior of atomic-scale particles. Unlike Newtonian physics, which is evident in our everyday experiences, the quantum realm challenges our intuition and perceptions of reality. Niels Bohr famously said, “Those who are not shocked when they first come across quantum theory cannot possibly have understood it.” This makes it particularly intriguing that quantum physics' complex and captivating principles shape the future of computing and information (Bruno, 2023).
The need for the emergence of quantum technology is a limitation in the current classical computation. For decades, the world has witnessed a boom in information technology and the ever-increasing computation power. Modern devices, with processing power over 100 times that of the best machines from the 90s, can now fit in your pocket (Bruno, 2023). The magic ingredient of this rapid revolution is transistors, along with their exponential increase, small size, and computational abilities.
“When classical computation reaches its limits, quantum technology emerges to redefine possibilities”
Our universe is inherently quantum mechanical, characterized by uncertainty and probabilistic behavior. Here is the intuition: suppose you are the size of an electron; throw a quantum ball, and you would probably see it going up rather than going down, and in the next attempt it may go down or left or right or even pierce through a closed window.
This breakthrough came with the advancements that paved the way for quantum technology. The idea sprang from Richard Feynman, who stated that the simulation of nature should be quantum mechanical, as we live in a quantum mechanical reality. His paper, “Simulating Physics on Computers,” hints at this direction. He writes, “Can a quantum system be probabilistically simulated by a classical (probabilistic, I’d assume) universal computer? In other words, a computer that will give the same probabilities as the quantum system does. If you take the computer to be the classical kind I have described so far (not the quantum kind described in the last section), and there are no changes in any laws, and there is no hocus-pocus, the answer is certainly, No! This is called the hidden-variable problem: it is impossible to represent the results of quantum mechanics with a classical universal device.” (Feynman, 1982)
In classical computers, a transistor is either on or off; "on" is represented as 1, and "off" is represented as 0 (Intel Education, n.d.).A classical computer works on the binary language of 0s and 1s. However, in quantum computation, their meaning is quite different. In this context, 0s and 1s are vectors written in Zeeman basis, representing the spin of an electron. For example, these states could correspond to the spin-up or spin-down motion of an electron, the polarization of a photon, or the ground and excited energy states of a particle. In short, it represents a two-level quantum system where only two distinct events are possible, and nothing else (Quantum Computation - an Overview | ScienceDirect Topics, n.d.).
Image from "Quantum Computing: A Taxonomy, Systematic Review and Future Directions" on ResearchGate https://www.researchgate.net/figure/Illustration-of-a-bit-and-qubit-Left-A-bit-can-take-a-value-of-0-or-1-with-100_fig5_344971320 (accessed September 25, 2024).
The definition of high computational power often misleads people into believing that quantum computers will excel at all tasks, such as predicting stock market trends or optimizing logistics. However, they do not necessarily perform simple classical tasks better or faster than classical computers. Quantum computers function on fundamentally different principles and hardware, specifically designed to address problems that classical computers find challenging. These include simulating complex molecular interactions for drug discovery, conducting nuclear magnetic resonance imaging (NMRI), and solving intricate optimization problems.
The potential of these computers is evident from the infamous Shor’s Algorithm developed by Peter Shor (1994), which can factorize large composite numbers. Its ability to factor numbers quickly poses a significant threat to widely used cryptosystems.
This is particularly important for RSA encryption, which secures global financial transactions by multiplying two large prime numbers. Since the product of two large prime numbers can only be factored by determining those original primes, factoring them efficiently using classical methods is nearly impossible. In this context, factoring means identifying the prime numbers, which would allow unauthorized access to encrypted internet communications. Years later, this algorithm continues to be the benchmark for quantum algorithms. Significant efforts have been made to safeguard global financial systems, national security, and other cryptographic applications (Quantum Cryptography - Shor’s Algorithm Explained, n.d.).
Another groundbreaking quantum algorithm is Grover's Algorithm, which transforms how we tackle search tasks. In classical computing, finding a specific item in an unsorted database of (N) entries typically requires a time-consuming, sequential check of each entry. In contrast, Grover’s Algorithm dramatically reduces this search time to the square root of (N). This significant speedup illustrates how quantum computers harness superposition and interference to navigate large datasets efficiently. While classical computers operate linearly, Grover's Algorithm capitalizes on the unique properties of quantum systems, emphasizing a fundamental shift in problem-solving approaches. This makes quantum computing a powerful asset in various fields, including cryptography, optimization, and complex data analysis (What Is Grover’s Algorithm?, 2020)
In conclusion, the journey into quantum computing is as exhilarating as it is challenging. IBM's significant contributions, particularly through Qiskit, have democratized access to quantum programming, enabling enthusiasts and researchers alike to run quantum programs on classical computers. This remarkable software library in Python serves as a gateway to understanding the complexities of quantum mechanics and its practical applications(Qiskit | IBM Quantum Computing, n.d.).
However, we must also recognize the ongoing challenges in this field. The race to advance quantum technology continues, with critical issues such as qubit decoherence posing significant hurdles. This phenomenon can alter a qubit's initial state, undermining the reliability of quantum computations. The efforts of industry giants like IBM, Google, PsiQuantum, Rigetti, Microsoft, D-Wave, and others highlight a collective drive towards overcoming these obstacles and unlocking the full potential of quantum computing.
Looking to the future, quantum computing holds the potential to bring the imaginative worlds of science fiction writers to life, enabling advancements that may currently seem unimaginable. The innovations on the horizon could revolutionize industries and create applications we have yet to conceive.
Works Cited
Bruno, A. (2023, August 8). What Is The Basic Relationship Between Quantum Physics & Quantum Computers? Planet Mainframe. https://planetmainframe.com/2023/08/what-is-the-basic-relationship-between-quantum-physics-quantum-computers/
Qiskit | IBM Quantum Computing. (n.d.). Retrieved September 25, 2024, from https://www.ibm.com/quantum/qiskit
Quantum Computation—An overview | ScienceDirect Topics. (n.d.). Retrieved September 25, 2024, from https://www.sciencedirect.com/topics/engineering/quantum-computation
Quantum Cryptography—Shor’s Algorithm Explained. (n.d.). Retrieved September 25, 2024, from https://www.classiq.io/insights/shors-algorithm-explained
What is Grover’s Algorithm? - Utimaco. (2020, May 12). https://utimaco.com/service/knowledge-base/post-quantum-cryptography/what-grovers-algorithm
Feynman, R. P. (1982). Simulating physics with computers. International Journal of Theoretical Physics, 21(6/7), 467-488.
Intel Education: Digital Information. (n.d.). Intel. Retrieved September 25, 2024, from https://www.intel.com/content/www/us/en/education/k12/the-journey-inside/explore-the-curriculum/digital-information.html.
Bretislav Friedrich, Dudley Herschbach; Stern and Gerlach: How a Bad Cigar Helped Reorient Atomic Physics. Physics Today 1 December 2003; 56 (12): 53–59. https://doi.org/10.1063/1.1650229
