Introduction

Why Quantum Computing?

We live in a world of increasingly complex systems, growing far too complicated and interconnected for any single person to understand. Perhaps we establish some small fiefdom in a field where we ‘get’ what’s going on, but cede control of other subjects to the so-called experts. We use mental models and heuristics to feel the contours of murky superstructures: Falling interest rates cause investment in the economy; growing transistor counts mean more powerful computers; increased renewable energy production means a greater need for grid-connected energy storage; et cetera.

As is so often true today, the most salient example of this is artificial intelligence. Most of us don’t quite know how large language models work. If forced to, I personally could say some things about linear algebra, tokens, and transformers; but my explanation would be incomplete at best and misleading at worst. Nevertheless, I know enough about large language models to navigate a world increasingly shaped by them. And it’s clear that this step – this ability to update our understanding of specific technologies and systems – is increasingly important. Imagine opening your internet browser in 2026 without knowing that text, images, and video could all be convincingly realistic but totally AI generated!

Enough about AI. As I’ve just noted, it’s more or less legible. I want to discuss a different technology whose fundamental hallmark is its illegibility. Of course, I’m talking about quantum computing (the title of this work does a poor job at building suspense!). If you’re reading this, you are probably familiar with the concept abstractly: a machine that utilizes quantum mechanics to perform computations – a quantum computer. As we’ll discuss, this kind of machine has been long-theorized, but has proven extremely hard to build. The field began with the ideas of physicists and mathematicians, acquired footholds in academic research institutions, and has since broken out into the world of commercial, for-profit ventures. The profile of the industry has risen dramatically in recent years, perhaps coupled with the trend of quantum computing startups going public.

Industry insiders and outside boosters regularly hail the revolutionary promise of quantum computation. The pace of PR from quantum startups and big players like Google is increasing; companies like IonQ are raising huge sums of money in the public markets; and there’s no shortage of quantum evangelists on LinkedIn or at conferences. And yet, people who understand the field are in short supply, and seem uniquely unwilling or unable to help the rest of us construct the correct mental model of the field. I’m serious! If you try to learn about LLMs, there is an endless supply of folks trying to teach you how transformers work from the ground up. There are dozens of highly technical people writing publicly about the semiconductor industry for generalist audiences. And from the quantum computing people? Crickets! Trust me, I’ve looked, and I’m being mostly fair in my characterization!

And so, here we are. Consider me your somewhat reticent guide to the world of quantum computing, dragged into this out of a sense of moral necessity. If the industry won’t explain itself, it falls to me to do so.

My personal interest in quantum computing began with reading various press releases posted on Hacker News (a generalist tech forum). I’m an electrical engineer with a PhD in power electronics. I’m perfectly used to having the typically software-focused posts on HN be incomprehensible to me, but these posts were more illegible than the norm. Moreover, the comments sections on these posts – usually relatively helpful – were instead marred by inter-commentariat bickering about the significance (or lack thereof) of the results in question. Consider my curiosity piqued: I wanted to know more about this whole quantum computing thing.

I also happen to be a deep-tech entrepreneur, and at an event in the summer of 2025, I happened to listen to a remarkably lucid pitch from a guy with a quantum computing startup. He seemed to be an exceptionally straight shooter who spoke specifically about avoiding the hype in the field. I approached him at the next break and introduced myself as a technically literate outsider who wanted to become ‘conversationally fluent’ in quantum computing. I asked him if he had any book recommendations for someone like me. He looked at me askance, paused a beat, and told me I could get a PhD in physics. Not quite the answer I was hoping for.

We live in an era dominated by hype cycles. It is par for the course that evangelists will tell us that some new technology will revolutionize the world. It is unfortunate but true that fortunes are built regardless of the veracity of those promises. We don’t have to go far back to remember the craze around NFTs – a technology that was on face absurd, but carried enough technical gravitas to legitimize investment (put charitably).

Quantum computing advocates have put out their fair share of weighty claims – purporting that the technology may be used for cryptography, material discovery, defense, handwriting analysis, finance, and much more. But more so than in other hype cycles, the actual technology here is so difficult to understand. To grasp what’s going on in the field, one must have a reasonable fluency in computational complexity theory, condensed matter physics, semiconductor engineering, and a half dozen other subjects. You have to wonder – will this industry, backed by billions in public and private capital, end up looking more like NFTs or like LLMs?

There are some helpful resources for learning about quantum computing as a layperson (Thomas Wong’s Introduction to Classical and Quantum Computing, Scott Aaronson’s writings, Michael Nielsen’s work), but they tend to focus on primarily the theory of computation. As an engineer, I’m interested in not only the theory, but the practical details of implementation. As an entrepreneur, I’m interested in the landscape of companies and where value might be created. As a member of society, I’m concerned billions are getting incinerated in a tech-washed financial scam. Finding no suitable explanation for the motivated layman, I’m writing one.

I hope for this to not compete with those other excellent texts, but serve as a complement. While I will discuss the foundations of computation, I hope to differentiate this work in a few ways: This text will aim to A) not harp on the details of the math and physics too much; B) provide a clear picture of the hardware landscape at this moment in time; C) explain the potential real-world applications of this technology; and perhaps most importantly, D) do all of this with a certain removed cynicism. I am not a quantum physicist; I am not employed by the quantum industry. I have no dog in the fight but admittedly, am a natural skeptic. This industry seems to have an infinite capacity for absorbing funding but struggles to communicate the ultimate value of their technology.

This book is written to answer the questions I have and to explain my conclusions to you, dear reader. Without further ado, let’s begin.

What is Quantum Computing?

To illustrate the difficulties in answering this question, let me try to pose an adjacent one: What is classical computing? Well – it’s obviously what happens when you organize billions of transistors into a complex system of interconnected memory and processing units. It’s just as obviously a branch of applied mathematics stemming from questions around computability and Turing machines. It’s software engineers and semiconductor companies and mathematicians and materials scientists and the billions of people who use their computers on a daily basis. Quantum computing is just the same – an amorphous blob of interrelated and competing stakeholders clustered around a particular ‘field’.

What makes quantum even more difficult to pin down is how much of the field is yet to be determined. To build a classical computer, we use semiconductor manufacturing processes that, while constantly evolving, all build on a multi-decade long lineage of linear improvements to photolithography. I can explain that to a motivated high school student. In quantum, there are at least a half dozen competing modalities for physical implementation of these devices, all with radically different advantages. Similarly, there are several wildly varied fields where quantum computing might be practically used, many of which aren’t very engaged with the quantum community itself.

Here’s my high-level overview of the different niches of quantum computing, all of which we will visit in greater detail later:

But admittedly, I’m dodging the original question. Here’s my simplistic answer: Quantum computing is a field that is trying to build, control, and use a new kind of computer that utilizes quantum mechanics.

History of Quantum Computing

Quantum computing, as its name suggests, straddles the divide between two very disparate fields.

Physicists have known about some of the strange manifestations of quantum mechanics on the macroscopic world for a long time – the famous double slit experiment, showing the wave-particle duality of light, was conducted in 1801! Over a period of about 150 years, quantum mechanics was shaped into a consistent theory by a murderer’s row of all-timer physicists like de Broglie, Heisenberg, Dirac, and von Neumann. During World War II, the field found a real-world application in the development of nuclear weapons as part of the Manhattan project.

WWII also served as a catalyst for the formalization and application of many theories related to computation, most notably in the field of cryptography (making and breaking codes). Alan Turing, famous for breaking the German enigma cipher, proposed the ‘Turing machine’ – a theoretical device with a strip of 0’s and 1’s, a printer, and a defined set of rules that could perform (or attempt to perform) computations. Today’s computers look nothing like Turing machines, but this thought experiment served as an important foundation for thinking about how efficiently machines could solve problems (more on this idea, called computational complexity later).

In 1980, several academics made the first steps to combine the two fields, seemingly independently. Paul Benioff described a ‘quantum Turing machine’ that could model Hamiltonians (governing equations of quantum systems). Soon after, Richard Feynman (Nobel prize winning physicist, bongo player, and safecracker, among other things) proposed that to efficiently simulate quantum systems, you could utilize a computer with quantum properties itself. Over in the USSR, mathematician Yuri Manin discussed using quantum mechanical phenomena to perform computations. People generally point to these proposals as the start of the discipline.

From here, it feels like the field is a snowball gradually picking up momentum as it rolls down a mountain. The 1980s experience gradual theoretical advancement, with the development of simple quantum algorithms (which we will discuss in greater detail later). David Deutsch publishes a seminal paper that concretizes several foundational principles in the field in 1985. In 1994, Peter Shor proposes an algorithm for the factoring of large numbers, which gives the field a ‘killer app’ (startup speak for financially valuable use case) – breaking encryption schemes! From here, government funding begins to pour into the field.

Now the experimentalists begin making some progress. In the mid-90s to 2010s, academics and national labs (in particular, the National Institute for Standards and Technology and Sandia National Labs) make significant gains in demonstrating various qubit modalities and operations on those qubits.

In 1999, the first (of many) quantum startups is created: D-Wave Systems, which is still alive today. D-Wave attempted to commercialize a very specific and limited kind of quantum computer, known as a quantum annealer, but has recently pivoted to being a more ‘normal’ quantum company (to the extent that any quantum company could be considered normal). Since then, quantum computing has drifted slowly into the mainstream. IBM has long been doing foundational quantum research, but other big companies have jumped into the ring, including Honeywell, Google, Microsoft, and Amazon. These days, quantum startups are a dime a dozen, with several having gotten large enough to go public: D-Wave, Rigetti, IonQ, Infleqtion, Quantinuum and others.

My antennas are finely tuned to the public consciousness, and I think the quantum computing industry is on the cusp of being ubiquitous. All the more reason, I figure, to properly understand it.

This Work’s Purpose

I am not a quantum physicist, nor a quantum computing expert. Reading this will not turn you into either. I’m convinced there is a sizable population who are intrigued by this beguiling topic who find the current mainstream media coverage facile and publications in the field incomprehensible. I hope this work to be a middle ground. I am aiming to approach the topic with intellectual rigor, but with the knowledge that I cannot possibly explain (or understand) the field at its complete depths. To that end, this work is limited in scope to four sections:

  1. COMPUTATION: What is quantum computation, and how does it differ from classical computation? What can quantum computers do in theory?
  2. IMPLEMENTATION: How does one build a quantum computer? What are the engineering challenges and constraints that make this difficult?
  3. APPLICATION: What would successfully developed quantum computers actually do?
  4. STATE OF PLAY: What does the field look like today?

My goal is to give you an idea of the contours of this field: a mental model for what quantum computing is today and could be in the future. Keep in mind that this is an extremely dense and technical subject, and you should not feel discouraged if you do not understand all the presented material at first glance. I invite you to focus on the sections that you are most excited or interested by, while encouraging you to at least skim the rest - theory, hardware, software, and applications are all very interlinked here. No matter what, I hope this text proves useful.

Acknowledgments and Resources

Let me re-emphasize: I am not a quantum physicist! In many ways, this text is a re-hashing of work done by others far smarter than I. My contribution, as I see it, is contextualization, organization, and an ability to translate heavy material to a more casual level. There’s obviously a huge amount of work that has educated me about quantum computing, much of it that I will cite in the following pages. However, I want to call out certain works that I think A) I’ve leaned on particularly heavily; B) serve as excellent introductions into their respective sub-fields: