Recently Google published a paper titled, Quantum supremacy using a programmable superconducting processor. In this paper, researchers detail how a quantum computer was able to outperform a classical computer in a computationally time intensive task. Specifically, they compare the performance of state-of-the art classical supercomputers to their quantum computer in the task of sampling random bitstrings (list of 0s and/or 1s like {0000101, 1011100, …}). Google’s quantum computer, called ‘Sycamore’, has a processor with 53 qubits. The processor is basically 53 loops of wire that have been cooled to a hundredth of a degree above absolute zero.
The Sycamore processor took 3 minutes and 20 seconds to complete the sampling calculation. According to Google, this same calculation would take a classical supercomputer 10,000 years to complete. IBM responded to Google’s claims stating that they can simulate Google’s results with a classical supercomputer in 2.5 days. The caveat here is IBM would need to use the Oak Ridge Supercomputer which is the largest supercomputer in the world. In his New York Times Opinion piece, Why Google’s Quantum Supremacy Milestone Matters, Scott Aaronson noted the significance of Google’s accomplishment despite IBM’s rebuttal:
We’re now in an era where, with heroic effort, the biggest supercomputers on earth can still maybe, almost simulate quantum computers doing their thing. But the very fact that the race is close today suggests that it won’t remain close for long. If Google’s chip had used 60 qubits rather than 53, then simulating its results **** with IBM’s approach would require 30 Oak Ridge supercomputers. With 70 qubits, it would require enough supercomputers to fill a city.
Classical Computers v. Quantum Computers
Why are quantum computers so much more powerful than classical computers?
Classical computers use binary digits (bits) which have values 0 or 1. These binary values correspond to two levels of low DC voltage (which is basically electric tension).
Quantum computers use quantum binary digits (qubits). Qubits arise when you cool electrons in wires to, in Google’s case 20 miliKelvin (very close to absolute zero), which causes them to behave quantum mechanically. As a result, qubits, or what I wittingly call cold bits, can assume states of 0, 1, or superpositions (linear combinations) of both. A superposition state corresponds to an equal probability of obtaining a binary value 0 or 1. This means that quantum computers have ‘in between states’ which allow them to capture quantum behavior like entanglement. Quantum entanglement is when two qubits are strongly correlated even at long distances, so much so that they seem to be communicating with each other faster than the speed of light. Because of quantum entanglement qubits can store much more information (up to two bits through superdense coding) and communicate much more information across long distances than ordinary bits. Entanglement lies at the heart of what makes quantum computers much more powerful than classical supercomputers.
What is Encryption and Where is it Applied
Encryption is the process of modifying a message, file and/or some data, so that only certain people with an encryption key can access the original information. Pre-encryption the data is called plaintext and post encryption the data is called cipher-text. Typically an algorithm is used to generate the cipher-text from the plain text as well as the key through the process of random number generation. A common method of encryption, and one of the most vulnerable to quantum computers, is the Rivest–Shamir–Adleman (RSA) algorithm which relies on the fact that finding factors of a large composite number is difficult.
Encryption has applications in securing shopping transactions, emails, online banking records, data on hard drives and passwords. Given the high security risk of these applications, it is a major concern if techniques are developed that can easily compromise data and information security.
What Threat Does Quantum Computing Pose for Encryption?
In Quantum Computing, an algorithm called Shor’s algorithm can be used to factor large composite numbers exponentially faster than classical computers. This ability means that with a powerful enough quantum computer you can easily crack encryption systems like RSA.
IBM Secures Data Encryption against Quantum computers
Instead of waiting for a powerful quantum computer to render all of our data insecure, IBM started developing encryption systems that protect against quantum computers. IBM approached the problem by first realizing that quantum computers are only good at solving a handful of tasks (one of them being factoring large composite numbers). The way to protect data against quantum computers would be to encrypt data using a problem quantum computers can’t solve. An example of such a problem is a "lattice problem." While lattice problems have been studied since the 1980s there is still no classical or quantum algorithm solution to them. This is an excerpt from the Scientific American article, New Encryption System Protects Data from Quantum Computers, regarding lattice problems:
One simple example of such a problem is to add three out of a set of five numbers together, give the sum to a friend and then ask that second party to determine which three numbers were added. "Of course, with five numbers, it’s not hard," Lyubashevsky says. "But now imagine 1,000 numbers with 1,000 digits each, and I pick 500 of these numbers."
While it is scary that quantum computers pose a huge risk to data security, it is reassuring that alternate methods to data encryption are currently being researched. While I personally found Google’s results very exciting, despite the risk implications, I think it is very important for safeguards to be put in place for data security. This is particularly true as we continue to generate more data along with growing technologies.
In this article, I discussed Google’s Sycamore processor and its ability to computationally outperform classical computers at a random sampling task. I discussed the concept of a qubit and how entangled states allow quantum computers to store more information than bits. This ability to store more information and communicate information faster allows it to outperform classical computers in tasks like composite number factorization. This has huge risk implications for encryption and data security. Finally, I discussed IBM’s effort to safeguard data encryption against quantum computers. I hope this article was useful and/or interesting. Thank you for reading!
