Written by: Shivam Kogar, Class of 2027
Edited by: Jacqueline Cho, Class of 2024
Image Source: LiveScience
Since it was theorized by Richard Feynman and Yuri Manin in the 1980s [6], quantum computing has driven curiosity, research, and innovation and has eluded many college students trying to gain a foothold on the topic. This curious field of study has brought theorists and engineers across disciplines together to explore the possibilities in this burgeoning field. Leveraging the phenomena of quantum mechanics, quantum computers perform calculations using ‘quantum bits’ or qubits, which are analogous to bits in classical ‘normal’ computers [2]. Quantum phenomena, when applied to computing, can theoretically provide significant computing advantages over classical computers, including increases in the speed of algorithms, and being able to solve harder problems that are increasingly difficult [3]. However, the rise of quantum computing raises important questions about whether we can actually bridge the divide between theory and reality. A world of quantum computers sounds promising, but is it actually a future we can realize?
We’ll start by asking the fundamental question: what is quantum computing and what distinguishes it from classical computing? Our typical classical bits carry values of ‘0’ and ‘1’, representing a logical state of either true or false. Representing variables and operations by series of 0s and 1s (think: binary code) has allowed us to do computations with modern classical computers. Qubits, however, work differently. A qubit can be thought of as holding both values of ‘0’ and ‘1’ at the same time. This is because of quantum superposition, a special property of particles to be in two states at once [3]. We can use the famous ‘Schrödinger’s cat’ thought experiment to understand this idea. If we have a cat in a sealed box, with a fifty-fifty chance of survival or death, quantum mechanics tells us that, as long as the box is sealed, the cat is simultaneously alive and dead. However, once we unseal the box, the cat ‘collapses’ into one of these two states. Our act of ‘measuring’ or ‘interfering’ with the cat is what causes it to collapse into a single state [6]. This notion of an object being in multiple states at once feels illogical and unintuitive but has been experimentally shown in the double slit experiment [link for further reading]. However, the crucial stipulation is that we cannot interfere with the object.
This means that nothing should touch our cat. Not even air, not even the cardboard surfaces of our box, nothing at all. How do we do this? First, we find an object which can have two opposite ‘cat states.’ Electrons have a magnetic property called ‘spin’ that is either ‘up’ or ‘down,’ and photons - light - can be polarized either vertically or horizontally. We assign one of these states ‘1’ and the opposite state ‘0’ [6]. And now we have qubits!
Next, we need to make sure that our qubits can indeed be in a superposition of both states. When we have any real-world system, we will always have ‘noise’ from the environment that will try to ‘interfere’ or ‘decohere’ our qubits, causing them to collapse into a single state.
We have objects called quantum gates that conduct operations on our qubits. In order to have a functional quantum computer, we need these quantum gates to conduct operations faster than “decoherence time,” or the time it takes for the noise to interfere with our qubits. In order to do this, we try to find ways to reduce noise or make it harder for the noise to affect our qubits. First, we choose qubits that are sufficiently small. Electrons and photons work because they are tiny enough so that particles moving nearby would have a lower probability of colliding with them, causing them to collapse into a single state. Another way to reduce noise is to put our qubits inside a container that is very cold (just above absolute zero, in fact), so that particles are moving so slowly that they have a very low chance of interfering with our qubits [6].
Reducing noise is one of the many engineering challenges that come with building a quantum computer. The materials needed are very difficult to source, and very few institutions have the materials engineering facilities to build a quantum computer. The quantum computers we have been able to build are still very ‘noisy,’ and so we try to mitigate this by adding extra qubits that have ‘error-correction’ capabilities [1]. In many ways, the theory of quantum computing has generated much excitement in the scientific community, as well as in political and industrial settings. For example, scientists have begun trying to use quantum computers to solve optimization problems - problems where we try and make systems more efficient - such as the management of supply chains, the management of road traffic, and the optimization of travel routes for airplanes. These problems are often complicated by a large number of variables, which invites the question of how we can find better ways to compute solutions [2]. While quantum computers have sparked the interest of many stakeholders, the practical realities of building a workable quantum computer raise the question of whether the theory of quantum computers maps to commensurate applications.
The field of quantum computing still has a long way to go. The theoretical advantages of quantum computation are sullied by the reality that quantum computers are really difficult to build. This raises the question of whether quantum computers actually have an advantage compared to classical computers. This idea is called ‘quantum supremacy’ or ‘quantum advantage’ [5], and scientists have proposed tests to see whether we have reached the stage where quantum computers are actually more powerful than classical computers. Proving a quantum advantage has two elements: (1) finding a problem that a quantum computer can solve substantially faster than a classical computer, and (2) building a quantum computer that would actually produce those results [7].
Even if we can’t identify a quantum advantage at this moment, scientists are motivated to keep trying. Engineers and materials scientists are continuously improving our quantum technologies, producing computers that can increasingly mirror theoretical models [5]. In this deeply interdisciplinary field, chemists, physicists, computer scientists, and mathematicians have come together in both academic and industrial settings with the shared goal of improving our technologies and sharing the belief that a quantum advantage might, someday, be proven. Until then, the excitement born with Feynman’s theories persists, and each day, our imagination inches closer to reality. We might not live in a quantum world today, but that doesn’t keep us from dreaming of a quantum world for tomorrow.
Works Cited
1. A new paper from IBM and UC Berkeley shows a path toward useful quantum computing [Internet]. IBM Research. 2023 [cited 2023 Nov 7]. Available from: https://research.ibm.com/blog/utility-toward-useful-quantum
2. Rubenstein B. Discussion on Progress and Future of Quantum Computing. 2023.
3. Giles M. Explainer: What is a quantum computer? MIT Technology Review [Internet]. 2019 Jan 29 [cited 2023 Nov 7]; Available from: https://www.technologyreview.com/2019/01/29/66141/what-is-quantum-computing/
4. Herbert S. From Double-slits to Qubits: A note for Quantum Computing [Internet]. University of Cambridge; 2020 Jan [cited 2023 Nov 7]. Available from: https://www.cl.cam.ac.uk/teaching/1920/QuantComp/From_double_slits_to_qubits.pdf
5. Smith-Goodson P. IBM’s Latest Research Paper Signals A New Era Of Quantum Computing Is Here. Forbes [Internet]. 2023 Jun 14 [cited 2023 Nov 7]; Available from: https://www.forbes.com/sites/moorinsights/2023/06/14/ibms-latest-research-paper-signals-a-new-era-of-quantum-computing-is-here/
6. Nielsen MA, Chuang IL. Quantum computation and quantum information. Cambridge; New York: Cambridge University Press; 2000. 676 p.
7. Swayne M. What Are The Remaining Challenges Of Quantum Computing? The Quantum Insider [Internet]. 2023 Mar 24 [cited 2023 Jul 11]; Available from: https://thequantuminsider.com/2023/03/24/quantum-computing-challenges/