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Ok, let’s address the elephant in the room.
Recently, Google hit the tape announcing the development of a 105-qubit superconducting processor chip named Willow.
And immediately, Bitcoin (and all of crypto) sold off. Bitcoin fell from roughly $104k to $92k on the news.
Bitcoin is a cryptographically secured network. Everyone is scared that this new quantum computer will crack Bitcoin’s cryptography.
Let’s take a look and find out.
Don’t worry; we will keep this at the layman level as much as possible.
Google’s announcement is a pretty big deal because according to Google, what makes the next-gen Willow chip so buzz-worthy is:
- It’s the first time that scientists have been able to crack a key challenge in quantum error correction after nearly 30 years of quantum research.
- They performed a standard benchmark computation in under five minutes that would take one of today’s fastest supercomputers 10 septillion (that is, 10^25) years — a number that vastly exceeds the age of the Universe.
Remember those two points as we move on.
But before we go too far down this Quantum Computing path, let’s make sure we understand what we are talking about.
I don’t want to get too nerdy here, but it is an important subject, so let’s tackle a high-level overview of quantum computing. I’m going to make this as understandable, while still informative as I can.
Regular computers use bits, they are like flipping coins – they can only land on heads or tails…they are binary.
Instead of bits (heads or tails), quantum computers use qubits (quantum bits).
Qubits are like magic coins that can spin in the air, being sort of heads and tails simultaneously. This special ability means they can solve certain complex problems much faster than regular computers, kind of like being able to check all possible answers at once instead of one at a time. However, they’re still very difficult to build, operate and maintain.
Quantum computers can process enormous amounts of data in ways that regular computers cannot. This makes them potentially excellent at solving certain types of complex problems, like breaking encryption codes, simulating chemical reactions for drug development, or optimizing complicated logistics networks.
From Google’s Blog post on their release of this information:
And:
Double Exponential growth rate made me stop dead in my tracks, and I had to write this down to understand it.
We have all heard of Moore’s Law and how classical computers improve the number of transistors on a microchip (which relates to computer power) doubles about every two years — or at least used to before they began running into physical constraints.
This is standard exponential growth.
Start with 2 transistors:
- Year 0: 2 transistors
- Year 2: 4 transistors
- Year 4: 8 transistors
- Year 6: 16 transistors
- Year 8: 32 transistors
But quantum computers are showing double exponential growth.
Starting with the same number of transistors:
- Year 0: 2 transistors
- Year 2: 16 transistors
- Year 4: 65,536 transistors
- Year 6: Around 4 billion transistors
- Year 8: 18,446,744,073,709,551,616 transistors (A number so large it’s hard to write out)
To put this in perspective, Moore’s Law at Year 8 would get us to just 32 transistors. Double exponential growth gets us to over 18 quintillion transistors in just 8 years.
For scale, this number is roughly 1,000 times larger than the number of grains of sand on all Earth’s beaches combined!
This means that while classical computers following Moore’s Law have made impressive progress (doubling every two years), quantum computers are advancing at a rate that makes even Moore’s Law look slow. However, it’s important to note that these quantum improvements are specific to certain types of calculations where quantum computers excel – they won’t necessarily beat classical computers in every task.
Also, while Moore’s Law proved remarkably consistent over many decades, quantum computing’s double exponential growth is still in its early stages. We’ll need to see if this dramatic growth rate can be maintained as the technology matures.
That’s a lot of transistors. But how many do we need for quantum computing?
To control and read just one qubit, you usually need several thousand transistors. This is because each qubit needs multiple control systems:
- Electronics to initialize the qubit
- Systems to read its state
- Error correction circuits
- Control systems to manipulate the qubit
- Temperature control systems (since qubits need to be kept extremely cold)
Currently, it takes anywhere from 1,000 to 10,000 transistors to control a single physical qubit. The exact number varies depending on the type of qubit being used (not gonna cover that here) and the specific quantum computer design (not gonna cover that here).
Now that we understand why the Google news was so exciting, we can understand why the crypto market got spooked on Monday following this news.
So, let’s see if these fears are warranted.
Okay, so how many cubits are needed to break Bitcoin?
Bitcoin’s security depends on the specific cryptographic component being targeted.
Everyone’s favorite story about how quantum computing makes Bitcoin worthless is that the entire Blockchain (the public ledger of all past transactions) is “hacked,” and the quantum computer rewrites (retroactively?) the entire Bitcoin Blockchain and moves all the Bitcoin into its own wallet.
This would make Bitcoin worthless because only the hacker with the quantum computer would have any Bitcoin. Who and why would anyone do this? Maybe a nation-state attacking a country with a lot of Bitcoin or someone who really hates Michael Saylor.
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A more plausible scenario involving a quantum hacker would be one where they intercept transactions and abscond with Bitcoin.
However, such scenarios remain impossible because these transactions have already been processed, moved, and often converted into other currencies. The Bitcoin blockchain serves as a historical ledger, recording every transaction since Bitcoin’s inception. Attempting to alter past transactions would be akin to time traveling to each specific moment in Bitcoin’s history.
Now that we’ve grounded ourselves in reality, let’s explore how a quantum computer could potentially hack Bitcoin.
If a hacker knows the public key associated with a transaction, they could theoretically hijack it by discovering the corresponding private key.
A quantum computer could leverage its capabilities to solve for this private key using the known public key, effectively allowing the hacker to steal the Bitcoin. Imagine it as a hacker knowing your username and then being able to deduce your password.
However, this isn’t an endeavor that can take forever. The Bitcoin blockchain is continuously updated with new blocks every 10 minutes. Therefore, the hacker must solve the cryptographic problem of the private key before the next block is added.
This means they have less than 10 minutes to crack the key if the transaction occurs at the start of a new block. This is why an incredibly fast and powerful computer—a quantum computer—is necessary.
This scenario illustrates how a quantum computer might hack Bitcoin. If the public key is known, researchers at the Centre for Cryptocurrency Research and Engineering at Imperial College London estimate that approximately 1,500 logical qubits would be required to break Bitcoin’s private key encryption using Shor’s algorithm (don’t worry about what that is).
Curious about logical qubits?
Stick with me here: there are two types of qubits—physical qubits and logical qubits.
Returning to our coin analogy: a physical qubit is like a real spinning coin, representing the actual hardware component within a quantum computer.
Just as real coins can topple or be disturbed, physical qubits are susceptible to errors. They are extremely delicate and can be affected by minor changes in temperature, vibrations, or other forms of interference.
In contrast, a logical qubit functions like a team of physical qubits working together to form a highly reliable unit. Imagine it as multiple people counting votes to ensure accuracy—if one person errs, the others can correct it.
Currently, creating one dependable logical qubit often requires hundreds or even thousands of physical qubits.
This is a significant challenge in quantum computing: we need numerous physical qubits to produce a smaller number of reliable logical qubits capable of performing accurate calculations.
With today’s quantum computing technology, around 1,000 to 10,000 physical qubits are typically needed to construct one reliable logical qubit, depending on the error correction method used.
Therefore, to achieve the 1,500 logical qubits necessary to solve the private key problem, we would require:
- At the low end (1,000 physical qubits per logical qubit): 1,500 × 1,000 = 1.5 million physical qubits
- At the high end (10,000 physical qubits per logical qubit): 1,500 × 10,000 = 15 million physical qubits
To put this into perspective, today’s most advanced quantum computers have around 100 to 1,000 physical qubits and are not yet capable of creating fully error-corrected logical qubits.
This is far from the 1.5 million to 15 million physical qubits needed to compromise a Bitcoin wallet if the private key were known.
This highlights the immense challenge of scaling up to large numbers of logical qubits. I won’t even delve into the complexities of operating a quantum computer with physical qubits, let alone achieving logical ones.
For enthusiasts like me, this is why Google’s advancements in increasing the number of qubits while simultaneously reducing errors are so exciting.
Given the complexity of this topic, it often attracts fearmongers and conspiracy theorists who thrive on its intricacies.
Bitcoin is the most secure network in the world. Quantum computers will have a very tough time cracking it. But… given the double exponential growth curve, it seems inevitable that over a long enough timespan, quantum computers will eventually be able to attack in this way.
This is why many proposals already exist for a quantum-resistant update to Bitcoin. Bitcoin core (the software) is updated regularly, with major updates every 6 to 7 months.
As quantum capabilities continue to improve, the quantum-resistant updates will eventually be implemented. It was designed, like any software, to be worked on and improved as technology advances.
An intriguing consideration is what a quantum computer could do to other, less secure cryptocurrencies or networks in general. This should be a greater concern than the potential impact on Bitcoin.
It’s tempting to draw parallels between the buzz around quantum computing and the meteoric rise of artificial intelligence—both are testaments to the relentless march of innovation.
But the difference lies in what quantum computing represents: the next frontier.
This isn’t just theoretical; it’s the trajectory of technology itself. Humanity builds tools not just to solve problems but to redefine the scale of what’s solvable. As we tackle the big questions with quantum precision, costs shrink, access grows, and the impossible becomes routine.
We’re not just observers of this progress—we’re part of the exponential curve. And with that, the future remains not only unpredictable but thrillingly ours
