What's Quantum Computing

All about bits, qubits, and super fast computers

The TL;DR

Quantum Computing is an experimental technology that uses quantum physics to do a whole bunch of tasks much faster than traditional computers.

• Traditional computers (like your laptop) rely on bits that can only be two things: 1 or 0

• Qubits – the quantum equivalent – can be both 0 & 1 at the same time, which means they can make super fast (at some things) computers

• Making qubits actually do stuff we want is hard (some need to be colder than space, some can only be controlled with tiny powerful lasers & all of them are unpredictable)

• The technology is still experimental, mostly run in labs by big companies like Google

It seems like quantum has been in the news more lately, especially with Google’s recent quantum chip release. So there has never been a better time to try and break it down!

(This is a guest post from Conor at Project Eleven, an applied quantum computing and cryptography lab. More on them later.)

Traditional computers: ones and zeros

Back in the 1600s, “computers” referred to clever people who could add more numbers in their heads than they had fingers or toes. Today, it usually means a device with a screen that runs apps, connects to the internet & sucks you into a regular doom scrolling session.

While they might seem worlds apart, both of these share a common core: behind every Instagram scroll or email is a series of mathematical operations. If computing is fundamentally about solving math problems, the next question is: can we find better ways to solve them?

Before diving in and answering this question, you first need to understand the basics of classical computers - the OGs of the modern computing world. For everyday tasks like sending emails, binging Netflix, or devouring cat videos, our modern “classical” computers do a stellar job. But how do they actually work under the hood?

At the most basic level, these machines speak a language of zeros and ones—bits. You can imagine them as tiny on (1) / off (0) switches. Flip them fast enough, and you can represent any piece of digital information—numbers, letters, entire video streams—all by combining those bits in the right pattern. The fancy terms you might’ve heard, like transistors, and processor cores (like CPUs and GPUs), are just ways of flipping those bits more efficiently or in special ways for certain tasks.

For example, here’s the word “computer” in binary:

01100011 01101111 01101101 01110000 01110101 01110100 01100101 01110010 00001010

Now, as amazing as these bit-flipping powerhouses are, they still run into a wall for certain problems: modeling huge molecules, finding insanely optimized routes through bustling traffic, or simulating the bizarre world of quantum physics. Classical machines either take ages or can’t even scratch the surface, because ultimately they handle tasks one (very fast) step at a time. At some point, you need a new approach—enter quantum.

Qubits: way more than ones and zeros

If the basic unit of a classical computer is the bit, then the quantum equivalent is the qubit (quantum bit)—and qubits have a knack for being… well, promiscuous. Unlike bits that stick to 0 or 1, qubits can be 0, 1, or any blend of both at the same time.

Picture a coin spinning endlessly in midair: it’s simultaneously heads, tails, and everything in between. This is called superposition. We don’t usually think of a flipping coin like this, but quantum mechanics insists that until you peek (measure), the coin is all outcomes at once. One interpretation, called Many Worlds, even suggests each unobserved possibility spawns a new universe. Yep, that’s right. Every time you flip a coin a new universe is created (maybe). You can literally be god from your desk (in theory).

If bits are the monogamous members of the computing world, qubits are the quantum Casanovas—exploring every possibility until the moment you measure them, at which point they settle down into a single reality. As bizarre as superposition sounds, the key point is that a single qubit’s ability to represent multiple values simultaneously allows it to store a significantly larger amount of information than a traditional bit.

Interference: the ripple effect

A qubit in superposition is powerful on its own, but the real magic happens when multiple qubits are used together. Multiple qubits can interfere with one another—like overlapping waves in a pond. We can exploit this interference so that “correct” answers build each other up (constructive interference) and “wrong” answers cancel out (destructive interference).

To see how different this is from classical computing, imagine a game show where you have a hundred doors to check, but only one of them holds the grand prize. A classical contestant opens the first door, sees no prize, moves on to the second, and so on—just extremely fast. If you want to go faster, you either add more classical contestants (a bunch of classical computers working in parallel) or you build a more powerful single classical contestant who checks doors more rapidly. But it’s still a one-door-at-a-time process.

A quantum computer, on the other hand, checks all doors at once, then uses interference to make the correct door stand out when it’s time to reveal the prize. It’s not magic—it still requires careful setup—but the key is that qubits can explore multiple possibilities simultaneously. By orchestrating superposition and interference in just the right way, quantum machines can often find the winning door in a single shot. That’s a radically different approach from brute-force checking, and it’s why quantum might solve some of our most complex problems a whole lot faster. But how do we control these qubits?

Quantum Gates: controlling the chaos

In a classical computer, bits pass through tiny electronic gates that flip them from 0 to 1 or combine them in straightforward ways—these gates effectively control the math of the classical system.

In a quantum computer, quantum gates perform similar operations like combining and flipping qubit values but can also do something far wilder. They can control how qubits move through their superposition of many possible values and how they interfere to reinforce or eliminate specific outcomes. In other words, quantum gates control the math of the quantum world.

Think of each quantum gate as a hand on two crucial knobs: superposition (how much 0 or 1 a qubit is blending) and interference (whether a qubit’s waves boost or cancel another’s). String enough of these gates together in the right order, and you have a quantum algorithm—a roadmap for turning “lots of possible answers” into “the right one” at measurement. Essentially, gates are how we transform “many possible answers at once” into “the right answer, right now”.

So what’s the latest?

At this stage, quantum computers are highly specialized machines housed in labs and look more like alien chandeliers than a classical computer. One of the biggest hurdles is fragility. Qubits require near absolute zero temperatures (-273.15 degrees Celsius/-459.67 degrees Fahrenheit) or near-perfect vacuums because even a trace of heat or stray radiation can knock them out of superposition. This is one of the biggest engineering challenges facing quantum computers today.

Beyond that, qubits are inherently probabilistic. Unlike their deterministic classical counterparts, you can nudge a qubit toward the correct answer, but sometimes it will still spin out a random result. Catching and correcting these slip-ups—called error correction—is another huge obstacle. Researchers are devising ways to use extra qubits that detect and repair errors on the fly, but it’s a delicate, resource-intensive process that is crucial to get right before we can build large scale quantum computers.

These obstacles may sound daunting, but they haven’t deterred companies like Google, IBM, Microsoft—and startups like IonQ, or PsiQuantum—from pouring billions into quantum computing. Even these early machines hint at solutions to problems classical computers struggle with, such as:

• Drug Discovery: Quantum simulations can handle molecular complexities that overwhelm classical machines, speeding up the design of new treatments and potentially shortening R&D timelines.

• Material Science: By accurately modeling atoms and their interactions, quantum computing can unlock advanced materials—from more efficient batteries to superconductors that revolutionize energy use.

• AI & Machine Learning: Quantum methods could accelerate training times and open up new model architectures.

• Encryption: Quantum computers can break current cryptography (including blockchains). Researchers are racing to develop “post-quantum” encryption that protects data against future quantum attacks. This is the initial focus of our work at Project Eleven - particularly protecting Bitcoin.

• Understanding Consciousness: for those among us who are philosophically inclined, a line of theories has arisen implying that consciousness is in some way a quantum state. Quantum computers could even help us reach a better understanding of ourselves.

While these breakthroughs are mostly proof-of-concept right now, the drive to refine and scale quantum systems continues—fueled by the promise of finally cracking challenges that have long stumped classical machines.

What does the future look like?

For now, quantum computers remain specialized machines tackling niche but high-impact tasks. Over time, industries like finance, logistics, and healthcare may adopt quantum methods behind the scenes—leading to faster drug discovery, more efficient supply chains, or stronger data security, all without altering your everyday scrolling habits.

But here’s the crux: quantum isn’t a quicker version of what we already have; it’s a different approach altogether. Where classical machines flip bits one by one, quantum harnesses superposition and interference to tackle problems bits can barely touch.

About Project Eleven

Project Eleven is an applied quantum computing and cryptography lab working to ensure the digital world is ready for the coming quantum era. Check them out and follow them on X.