Microsoft Research
12 HN recommenders · recommended in 15 months, 2018–2025
1:28:23 · 2.2M views · May 14, 2018
An 88-minute Microsoft Research talk that explains how quantum computers beat classical ones using basic linear algebra, qubits, superposition and gates. It works through the Deutsch oracle problem and ends with entanglement, teleportation and a live demo.
It is HN's most frequently recommended starting point for quantum computing because it avoids pop-science hand-waving and needs only basic linear algebra.
20 comments from Hacker News
The Quantum Computing for Computer Scientists video by Microsoft Research ( this video ) really hammered it home for me. It goes slowly and the presenter, in his own words "shuts up and does the math".
this video This video is the simplest explanation that I have found for Quantum Computing which doesn't do the whole pop-sciency "is both zero and one at the same time" nonsense.
Learning Quantum Computing based on skill level (math is the biggest friction point, suggested pdf should save you lots of time) (Recc is personal recommendations, Hi-Recc is look at ASAP) # QC Main Ideas - Rotate, Compute, Rotate - Think in Amplitude Interference # Beginner: -(Hi-Recc) Quantum Computing Primer (1.5hr) : this video -(Hi-Recc) Math Primer for Quantum Computing (easiest intro/primer I found on the topic; Highly Recommend ) : [LINK] -- understand Bra Ket notation [<Bra|Ket>] (Ket as Column vector, Bra (Row vector) as Complex Conjugate of Ket (denoted as dagger) ) -- understand Kronecker product ( for multi-qubit systems) - Quantum Computing for Computer Scientists book - [LINK] - Quantum Math Primer (Faculty of Khan) (found a bit hard the first time around, pretty dense) : [LINK] # Intermediate -(Recc) Ryan O'Donnell CMU course [is the best if you want to really understand the capabilities of quantum computing, get practice with math, intuition] (algos connection to Fourier, Quantum Complexity Theory, Math best practices, learning multi-quibit systems) -- Quantum Computation and Information at CMU : [LINK] -- Lecture Notes (use as reference in case video is not clear, or camera shot lags/changes) [LINK] - Mermin's Textbook [LINK] - Nielsen & Chuang's Textbook [LINK] -- Nielsen's Lectures [LINK] # Advanced -(Recc) Scott Aaronson Graduate Course [LINK] -(Recc) Scott Aaronson Papers (really interesting) [LINK] - Complexity Zoo - List of Algorithms [LINK] -(Recc) Machi
The shortest possible answer is that qubit states are modeled as two-dimensional vectors on the complex unit sphere. We arbitrarily designate two orthonormal vectors on this sphere as corresponding to classical states 0 and 1. If the qubit vector isn't in the 0 or 1 state, it's in some linear combination of them. This is called superposition. Since most people don't know what linear combination means, superposition is explained as "sort of both at the same time". Upon measurement the qubits are collapsed to 0 or 1 with some probability proportional to how close they are to the 0 and 1 states. The precise probabilities are given by something called the Born rule. I gave a longer talk aimed at computer scientists if you're interested beyond this explanation: this video
> what is programming a quantum computer like? You compose a series of gates that manipulate the state qbits to perform calculation. My understanding is that these gates can be abstracted in a somewhat familiar programming language environment. I've got a very rudimentary understanding, my crude summary would be: it's basically applied linear algebra, leveraging the properties of superposition to perform some types of computations more efficiently. Namely, reducing some search spaces to sqrt n. This video is a good hands on intro: this video