Quantum computers could cause unprecedented disruption, both for good and ill, from cracking the encryption that protects our data to solving some of the most complex puzzles in chemistry. new research has given us more clarity on when that might happen.
Modern encryption schemes are based on fiendishly difficult mathematical problems that even the largest supercomputers would take centuries to crack. but the unique capabilities of a quantum computer mean that, given enough size and power, these problems become simple, rendering current encryption useless.
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That’s a big problem for cybersecurity and it’s also a big challenge for cryptocurrencies, which use cryptographic keys to protect transactions. If someone could crack the underlying encryption scheme used by bitcoin, for example, they could forge these keys and alter transactions to steal coins or carry out other fraudulent activities.
This would require much larger quantum computers than we have today, but exactly how large they are is unclear. A new paper in Quantum Science AVS from researchers at UK startup Universal Quantum has revealed that a machine with 317 million to 1.9 billion qubits would be needed to crack bitcoin.
the range of qubits is wide because there is a variable window within which 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 lower end of that scale could pick out a few transactions, but only 1.9 billion qubits would guarantee that it could target all of them. sometimes transactions can take up to a day, in which case the researchers calculated you’d 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 carry out a single operation or the number of errors that get into calculations can vary significantly depending on the specific type of hardware used to build the quantum computer, and these factors can have a big impact on how much of qubits needed. .
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To solve this problem, the researchers created a tool that takes these hardware characteristics into account when calculating the required size of a device for a specific problem. The figures above refer to a machine with operating times of one microsecond, which is typical for superconducting quantum computers being built by Google and IBM.
trapped ion devices, favored by universal quantum, ionq and honeywell, have operating times of around 235 microseconds. for those relying on silicon qubits, times can go up to milliseconds, which can significantly increase the number of qubits needed.
Researchers also investigated another problem where quantum computers are expected to outperform conventional ones: simulating molecules. the enormous complexity of calculating interactions between even small numbers of particles means that most chemical models are based on approximations, and even these require supercomputers. But quantum computers play by the same rules as atoms and molecules, so with enough qubits, they should be able to perform exact simulations within reasonable time frames.
A promising target for such modeling is the femoco molecule that some plants and microorganisms use to fix nitrogen from the air. understanding how it works could lead to massive efficiency gains in fertilizer production, an industry that currently uses two percent of the world’s energy supply.
Conventional computers are unable to simulate the molecule, but the researchers found that a superconducting device could solve the calculations in 10 days using just 7.5 million qubits. with the same number of qubits, a trapped ion device would take 2,450 days, which is probably impractical, but you can achieve a 10-day response time with a 600 million-qubit machine.
however, the specific design that universal quantum is targeting has a trick up its sleeve. superconducting qubits can only talk directly to their neighbors, and any long-range communication requires daisy chains of message-passing interactions that can absorb many operations. in contrast, trapped ion computers can physically transport their qubits to allow them to directly interact over much greater distances.
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This reduces the number of operations required, 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 in superconducting devices.
Either way, research suggests that both bitcoin cracking and solving nitrogen fixation are probably still a long way off. and more importantly, it shows that scalability is going to be very important for quantum computers, particularly those based on trapped ions, which are likely to need many more qubits than their superconducting competitors.
image credit: darwin laganzon from pixabay
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