Quantum computers could crack Bitcoin. Here’s what it would take

Quantum computers could cause unprecedented disruption, both good and bad, from cracking the encryption that secures our data to solving some of chemistry’s most intractable puzzles. New research has given us more clarity on when this might happen.

Modern encryption schemes rely on extremely difficult mathematical problems that would take even the greatest supercomputers centuries to solve. But the unique capabilities of a quantum computer mean that given enough size and power, these problems become simple, making current encryption unnecessary.

This is a big problem for cybersecurity, and it also poses a major challenge for cryptocurrencies, which use cryptographic keys to secure transactions. If someone could crack the underlying encryption scheme used by Bitcoin, for example, they could tamper with those keys and alter transactions to steal coins or conduct other fraudulent activities.

It would be rrequire much larger quantum computers than we have today, but their exact size is unclear. A new paper in AVS Quantum Sciences of rResearchers from the British startup Universal Quantum calculated that it would take a machine with 317 million at 1.9 billion qubits to crack Bitcoin.

The range of qubits is large because there is a variable window withwhere transactions are vulnerable. This is while they wait to be processed, which normally takes between ten minutes and an hour. A quantum computer at the low end of this scale would be able to detect some transactions, but only 1.9 billion qubits would guarantee that you could target them all. Sometimes transactions can take up to a day, in which case the researchers calculated that you would only need 13 million.

It is important to note that these figures relate to a specific type of quantum computer. Things like the time it takes to perform a single operation or the amount of errors that creep into calculations can vary greatly depending on the specific type of hardware used to build the quantum computer, and these factors can have a big impact on the number of qubits required.

To get aAround this, the researchers created a tool that takes these hardware characteristics into account while calculating the size of a device needed for a specific problem. The numbers above are for a machine with microsecond run times, which is typical for superconducting quantum computers built by Google aD IBM.

Trapped ion devices, favored by Universal Quantum, IonQ, and Honeywell, have operating times closer to 235 microseconds. For those that rely on silicon qubits, times can reach milliseconds, which can significantly increase the number of qubits required.

The researchers also studied another problem where quantum computers are supposed to blow conventional computers out of the water: the simulation of molecules. The enormous complexity of calculating interactions between even a small number of particles means that most chemical modeling relies on approximations, and even these require supercomputers. But quantum computers are governed by the same rules as atoms and molecules, and so with enough qubits they should be able to perform exact simulations in reasonable time.

A promising target for such modeling is the molecule FeMoco, which certain plants and microorganisms use to fix nitrogen from the air. Understanding how it works could lead to massive efficiencies in fertilizer production, an industry that currently uses of them % of world energy supply.

Conventional computers are unable to simulate the molecule, but researchers found that a superconducting device could solve calculations in 10 days using just 7.5 million qubits. Using the same number of qubits, a trapped ion device would take 2450 days, which is probably not practical, but you can get 10 days with a 600 million qubit machine.

the Universal Quantum specific design aims at a trick up his sleeve, however. Superconducting qubits can speak directly only to their neighbors, and any long-range communication requires chains of message-passing interactions that can absorb many operations. In contrast, trapped ion computers are able to physically move their qubits to allow them to directly interact over much greater distances.

This reduces the number of operations needed, which in turn should reduce the number of qubits needed. More importantly, it could open the door to new error correction schemes that could be considerably more efficient than those used on superconducting devices.

Either way, the research suggests that cracking Bitcoin and solving nitrogen fixation is likely still a long way off. And more importantly, it shows that scalability is going to be hugely important for quantum computers, especially those based on trapped ions, which are likely to need many more qubits than their superconducting competitors.

Image credit: Darwin Laganzon from Pixabay