Update (April 19): Apparently a bug has been found, and the author has withdrawn the claim (see the comments). For those who don't yet know from their other social media: a week ago the cryptographer Yilei Chen posted a preprint, eprint.iacr.org/2024/555, claiming to give a polynomial-time quantum algorithm to solve lattice problems. For example, it…
[By prior agreement, this post will be cross-posted on Microsoft's Q# blog, even though it has nothing to do with the Q# programming language. It does, however, contain many examples that might be fun to implement in Q#!] Why should Nature have been quantum-mechanical? It's totally unclear what would count as an answer to such…
I've supervised a lot of great student projects in my nine years at MIT, but my inner nerdy teenager has never been as personally delighted by a project as it is right now. Today, I'm proud to announce that Adam Yedidia, a PhD student at MIT (but an MEng student when he did most of this work),…
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IMAGE: Scott Aaronson, a Professor of Computer Science at the University of Texas, Austin, has been selected as the recipient of the 2020 ACM Prize in Computing. Aaronson is recognized for. view more
Credit: Association for Computing Machinery
ACM, the Association for Computing Machinery, today announced that Scott Aaronson has been named the recipient of the 2020 ACM Prize in Computing for groundbreaking contributions to quantum computing. Aaronson is the David J. Bruton Jr. Centennial Professor of Computer Science at the University of Texas at Austin.
The goal of quantum computing is to harness the laws of quantum physics to build devices that can solve problems that classical computers either cannot solve, or not solve in any reasonable amount of time. Aaronson showed how results from computational complexity theory can provide new insights into the laws of quantum physics, and brought clarity to what quantum computers will, and will not, be able to do.