Bitcoin Magazine

The Quantum Issue: WTF Is Quantum Computing?

What is quantum computing? How is a quantum computer different from a regular computer? What relevance does this have to Bitcoin?

New Bitcoiners have been inevitably bumping into these questions and having to confront the issues they dredge up regarding Bitcoin’s exposure to what is very much an existential threat to its existence if a viable quantum computer were to be developed. 

The ability to own bitcoin rests on the foundational assumption that without directly leaking a copy of it, no one but the person who possesses a private key can sign to transact with coins secured by that key. Quantum computing calls that assumption into question. 

Quantum computers are not just “computers, but faster.” They function in a very fundamentally different way from a classical computer, and as such they are much more efficient than classical computers at very specific kinds of computations. Now obviously, I’m not going to actually explain how quantum computers work in minute detail within four pages, but I will give you the core intuition of how they are fundamentally different from a classical computer. 

So let’s take a look at how both kinds of computers interact with things like large cryptographic keys. 

Classical Computers

Everything stored in a classical computer (or just computer from here on out) is stored as a series of 1s and 0s. Each bit (1 or 0) is precisely a 1 or 0; there is no ambiguity. When a piece of data is stored, it’s 1s and 0s. When a piece of data is manipulated or modified, it is done bit by bit, step by step, on each 1 or 0. 

That is how a computer works. It linearly, one step after the other, modifies the discrete unambiguous pieces of data that it is storing. It can’t skip ahead, or shortcut (in terms of the steps it’s taking, not more efficient ways to do things mathematically), it has to go through the steps of whatever computation it is doing one by one. 

When you generate a private key using a computer, it acquires a random value (you inputting dice, general user input, randomness from device hardware, etc.) and stores that in memory as 1s and 0s. From there it has to multiply this value by the elliptic curve’s generator point to get a public key. This is accomplished with an algorithm, that boiled down to its most basic level, is literally instructions on what bits to take, how to modify them, what circuits to “push” them down on a physical level to accomplish that, and in the end put the new value that has been modified bit by bit back into memory. 

There are other steps to arrive at an actual valid address, but for the purposes of this article those are not necessary to go into (but they are just like the above step, just step by step instructions on how to modify 1s and 0s in memory). 

So what if someone wanted to use a computer to guess someone else’s private key? 

There are 2²⁵⁶ possible private keys. That’s 115,792,089,237,316,195,423,570,985,008,687,907,853,269,984,665,640,564,039,457,584,007,913,129,639,936 different possible keys. 

A computer would have to try every single one of those possible private keys, one after the other (or however many at a time it can do in parallel), step by step following the exact instructions above for generating keys. The more of them you try to check in parallel, the more computing power you need, with no ability to find any shortcuts around that cost. 

The less computing power you want to use, the more time it will take, the less time you want it to take, the more computing power you need. 

This is an impossible task to accomplish with a computer. On one side you have a computation cost that every computer on Earth is not enough to pay, and on the other side you have a cost in time that is so high every star in the universe would die before you checked them all. 

To actually accomplish your goal, you need another option besides checking one by one linearly or in parallel. That’s where quantum computing comes in.

Quantum Computers

Quantum computers don’t work with discrete states. Everything is precisely a 1 or a 0. The most basic piece of information in a quantum computer is a qubit (the quantum version of a bit). Unlike a bit, a qubit is in a superposition where it is both simultaneously a 1 and a 0. It only settles into one or the other discrete states when it is observed. 

This is one of the key building blocks that allow a quantum computer to compute differently. The other is entanglement. Qubits aren’t just stored in isolation, the physical atoms representing them and collapsing to a discrete state when observed are entangled together. This means when entangled atoms are observed and collapse to a single state, the entangled atoms collapse to the same state, no matter how far apart they are. 

Now here’s where things get weird, and I’m going to have to get a little hand-wavy; you should still walk away with an intuitive understanding of why quantum computers are fundamentally different from a classical computer. An algorithm on a classical computer is a set of instructions to take a specific set of bits, and step by step modify them according to the algorithm’s instructions, until finishing and outputting the finished set of new bits. So the algorithm step by step takes one discrete state and turns it into another. 

Qubits don’t store discrete states until they are observed and collapse to one. They store probabilities. When you have a set of qubits entangled of any given size (like in this hypothetical case 2²⁵⁶), each given possible state that it collapse to has a certain probability of collapsing to that given state. 

Quantum algorithms, rather than being step by step instructions to operate on discrete states, are a set of instructions on how to operate on those entangled qubits in a way that alters the probabilities of different outcomes. Constructive interference is used to increase the probability of a correct outcome, and destructive interference to decrease the probability of incorrect outcomes (note that this is NOT the noise or interference that makes it difficult for physical quantum computers to function accurately, that is a different concept). 

So while a classical computer would have to check each individual private key one by one to find the one matching a specific public key, a quantum computer can simply run a few times using the right algorithm and arrive at the correct answer. It does not do this by “checking all the possibilities at once.” It simply modifies the probabilities of what a superposition will collapse into. 

This is why a quantum computer could break the assumptions underlying elliptic curve cryptography, and a classical computer could not (and it is also why quantum computers are only useful for certain types of computations with a massive possible space of answer candidates to check). 

Don’t Panic

This fundamental difference between classical and quantum computation means, that yes, if a viable quantum computer is actually produced, that functions correctly, then the underlying assumption that secures all Bitcoiners’ individual bitcoin is broken. All of those funds are insecure. 

Yes, this is a serious risk if such a device is actually manufactured, and it works, but we are not entirely unprepared. We understand the problem, we understand the exposure, and a good number of possible solutions to many different facets of the problem are coming together. 

Breathe, and relax. Through the rest of this issue we are going to walk you through the whole problem. 

This piece is featured in the latest Print edition of Bitcoin Magazine, The Quantum Issue. We’re sharing it here as an early look at the ideas explored throughout the full issue.

This post The Quantum Issue: WTF Is Quantum Computing? first appeared on Bitcoin Magazine and is written by Shinobi.

Bitcoin Magazine

The Quantum Issue: Letter From The Editor

Quantum this, quantum that…who put a stupid cat on-chain!?

Ahem. 

Alright, let’s be serious. The threat that a viable, actually functioning, quantum computer would pose to Bitcoin if it were to be built is very serious. It is the concrete example of an existential threat, in every sense of the word. 

One of the bedrock foundations that Bitcoin rests upon is the assumption of a functioning cryptographic system that can be used to produce unforgeable signatures, i.e. that if you follow that system’s protocol properly when signing things, there is no way that anyone but a bitcoin’s rightful owner could produce a signature needed to spend it unless the rightful owner failed to secure their private key from theft. 

Quantum computers toss that right out the window. There goes the integrity of the entire mechanism that is used for owners of bitcoin to authenticate their ownership for the protocol to process their legitimately authorized transactions, and ONLY their legitimately authorized transactions. There’s no way for anyone to actually own anything in the context of the Bitcoin protocol if that assumption breaks. 

Bitcoin breaks if that assumption breaks. 

Thankfully, there are many different cryptographic systems that exist, and not all of them rest on assumptions that a quantum computer breaks. That’s the good news. The bad news is that its all a set of tradeoffs, none of them are ideal, and there are going to be some hard choices that have to be made. 

But there are solutions to just about every one of the problems that a viable quantum computer would create…except the problem of choosing which solutions to use. So in light of that, here is The Quantum Issue. 

This issue is a lot more structured than most past issues, and that is to ensure that it guides a reader through the entirety of the problem space and solution space without assuming any prior understanding (this is a very deep and technical subject). 

The first set of articles goes through the general issue of quantum computing itself, how it differs from classical computing, why that matters, how likely it is one is developed soon, etc.

The second set examines Bitcoin’s exposure. How is it exposed? How badly is it exposed? How can that degree of exposure change? 

The third set examines concrete (or developed enough to not be too hard to get to a concrete place) solutions to securing your bitcoin in a quantum safe way, and handling a network wide migration to those solutions. 

Don’t miss your chance to own The Quantum Issue — featuring articles written by many influential figures in the space working on the necessary pieces for a post-quantum Bitcoin!

This piece is the Letter from the Editor featured in the latest Print edition of Bitcoin Magazine, The Quantum Issue. We’re sharing it here as an early look at the ideas explored throughout the full issue.

This post The Quantum Issue: Letter From The Editor first appeared on Bitcoin Magazine and is written by Shinobi.

When it comes to 3D printing in the FDM world, you can go a long way just relying on standard settings that ship with your 3D printer and/or slicer. If you want to push the limits, though, it pays to better understand the hardware and materials you’re working with to know what you can get away with. To that end, [Robert Samples] put together the MeltCalc database to help. 

The purpose of MeltCalc is simple—it collates data on hot ends and materials regarding factors like maximum flow rate, print speeds, and heater requirements. If you’re wondering whether a given hot end can flow a given filament at a given rate, for example, this tool is a great place to start. It features 64 different hot ends and 36 polymers typically used in the 3D printing world, and can spit out maximum flow rates and print speed estimations even accounting for fancy tech like Core Heating Technology (CHT) nozzles. It’s all based on thermodynamic modelling which [Robert] put together based on his experience as a chemist who works with polymers. His aim was to provide a tool with realistic flow rates for hot ends, so that end users don’t have to just rely on often-optimistic marketing numbers.

For those eager to dive deeper into the code and modelling, the project source is available on Github. We’ve featured all kinds of other useful hacks in this space lately, too, like our recent look at how to achieve wave overhangs. If you’ve got your own nifty 3D printing tools in the works, don’t hesitate to notify the tipsline.

Compare iris recognition and fingerprint biometrics in 2026, from accuracy and speed to security, privacy, and where each technology works best.