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Algorithmic Assertions
Algorithmic Assertions is a computer science blog. Posts are usually technical, on the order of a couple thousand words long, and focused on some idea in mathematics, software engineering, algorithmic complexity, quantum computing, or computers in general.
19 days ago by cierniak
Google has enlisted NASA to help it prove quantum supremacy within months - MIT Technology Review
The firm will pit its Bristlecone quantum processor against a classical supercomputer early next year and see which comes out on top.
quantum-computing  nasa  google 
5 weeks ago by hschilling
Shtetl-Optimized » Blog Archive » Lecture notes! Intro to Quantum Information Science
In Spring 2017, I taught a new undergraduate course at UT Austin, entitled Introduction to Quantum Information Science.  There were about 60 students, mostly CS but also with strong representation from physics, math, and electrical engineering.  One student, Ewin Tang, made a previous appearance on this blog.  But today belongs to another student, Paulo Alves, who took it upon himself to make detailed notes of all of my lectures.  Using Paulo’s notes as a starting point, and after a full year of procrastination and delays, I’m now happy to release the full lecture notes for the course.  Among other things, I’ll be using these notes when I teach the course a second time, starting … holy smokes … this Wednesday.
syllabus  quantum-computing  computer-science  class  to-read 
5 weeks ago by Vaguery
Quantum Cryptography School for Young Students (QCSYS)
The Quantum Cryptography School for Young Students (QCSYS) is a unique, eight-day enrichment program for students hosted by the Institute for Quantum Computing (IQC) at the University of Waterloo.
The school offers an interesting blend of lectures, hands-on experiments and group work focused on quantum cryptography — a cutting-edge field that utilizes the fascinating laws of quantum mechanics to develop unbreakable encryption that protects communication.
high-school  summer-camps  quantum-computing 
6 weeks ago by cierniak
A Guide to Post-Quantum Cryptography
Post-quantum cryptography is an incredibly exciting area of research that has seen an immense amount of growth over the last decade. While the four types of cryptosystems described in this post have received lots of academic attention, none have been approved by NIST and as a result are not recommended for general use yet. Many of the schemes are not performant in their original form, and have been subject to various optimizations that may or may not affect security. Indeed, several attempts to use more space-efficient codes for the McEliece system have been shown to be insecure. As it stands, getting the best security from post-quantum cryptosystems requires a sacrifice of some amount of either space or time. Ring lattice-based cryptography is the most promising avenue of work in terms of flexibility (both signatures and KEM, also fully homomorphic encryption), but the assumptions that it is based on have only been studied intensely for several years. Right now, the safest bet is to use McEliece with Goppa codes since it has withstood several decades of cryptanalysis.
cryptography  crypto  post-quantum-crypto  pqc  quantum-computing  via:el33th4xor  security  algorithms 
7 weeks ago by jm
[1803.10908] Matrix Product Operators for Sequence to Sequence Learning
The method of choice to study one-dimensional strongly interacting many body quantum systems is based on matrix product states and operators. Such method allows to explore the most relevant, and numerically manageable, portion of an exponentially large space. It also allows to describe accurately correlations between distant parts of a system, an important ingredient to account for the context in machine learning tasks. Here we introduce a machine learning model in which matrix product operators are trained to implement sequence to sequence prediction, i.e. given a sequence at a time step, it allows one to predict the next sequence. We then apply our algorithm to cellular automata (for which we show exact analytical solutions in terms of matrix product operators), and to nonlinear coupled maps. We show advantages of the proposed algorithm when compared to conditional random fields and bidirectional long short-term memory neural network. To highlight the flexibility of the algorithm, we also show that it can readily perform classification tasks.
representation  machine-learning  to-understand  matrices  quantum-computing  classification  algorithms 
8 weeks ago by Vaguery

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