Quantum Computing for Everyone

Author: Chris Bernhardt
Publisher: MIT Press
ISBN: 978-0262039253
Print: 0262039257
Kindle: B07P7KN23F
Audience: People interested in quantum computing
Rating: 4
Reviewer: Mike James
Quantum computing for everyone is a tall order, can it be delivered?

I will put you out of your misery - no it cannot.

This shouldn't come as a surprise and perhaps the book really shouldn't promise the impossible. Quantum mechanics is difficult stuff to understand and quantum computers make it seem even harder. Before I scare you off reading this review I'd better say that this is a good book and you might well want to read it - but only if you don't faint at that sight of an equation. A book designed "For Everyone" really should keep away from equations, and math in general, but this one doesn't. Strangely though it does make a promise at the start not to use complex numbers. Why I have no idea because it dives into bras, kets, orthogonality, matrices, vectors, the scalar product, the tensor product and more. I opened a more or less random page in the middle of the book and showed it to a non-math person and they recoiled in horror. Why save the reader from complex numbers if you are going to inflict the rest? Not using complex numbers makes arguments about phase much more difficult, so there isn't much of a win. 

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Chapter 1 starts off with a look at some basic physics via the Stern Gerlach experiment. For me this didn't really bring the strangeness of quantum mechanics to the surface. You really need the concept of an eigenstate and mixtures of eigenstates to understand it, even if you aren't presented with the mathematics of eigenstates and values. It can be done simply and non-mathematically.

Chapter 2 introduces linear algebra and this is just a simple introduction to not-quite-enough math to understand quantum states and measurement. It introduces vectors and then bras and kets and the inner product is revealed as what you get when you write a bra next to a ket - which is novel, but potentially confusing. The chapter goes though basic linear algebra including matrices, but not the tensor product.

 

Our first foray into quantum physics proper is in Chapter 3 where spin and polarization are used as examples of qubits. After this, in Chapter 4, we move into the subject of entanglement, which is probably the most sophisticated of all quantum ideas. Here we do meet the tensor product and I'm not sure that there is an easier way of dealing with entangled states. This and the next chapter do a reasonable job of convincing the reader that entanglement is strange and that Bell's inequality proves that it cannot be explained away. You can spend a long long time pondering entanglement and just when you think you see why it is strange you have to start over. Entanglement is what makes a quantum computer more powerful than a classical one.

Chapter 6 introduces the idea of classical gates and circuits. Even if you know your Boolean algebra this could be new to you. The key difference is reversible computing as quantum computers are composed of reversible gates. Chapter 7 introduces the quantum equivalents of the classical gates and more. There are also some nice easy to understand examples of simple quantum systems providing almost practically useful facilities - superdense coding, quantum teleportation and error correction. Chapter 8 moves on to more advanced quantum algorithms and introduces the ideas of P and NP. Next we have Deutsch's algorithm which is the easiest example of a quantum computer doing something faster than a classical computer. This one is so easy to understand, but it still has the power to keep you awake at night wondering where the extra power actually comes from.

The final chapter is the one that is supposed to convince the reader that the quantum computer is going to shake things up. We have Shor's factoring algorithm and Grover's search algorithm. Neither are explained in detail but you should come way impressed that someone, even a quantum physicist, thought these up. Really clever quantum algorithms are hard to invent. The chapter closes with a look at quantum chemistry (is there any other kind) and the hardware needed to create a quantum computer. The book closes with some philosophical thoughts culminating in "all computers are quantum".

If you aren't afraid of math, and perhaps know some quantum mechanics, then this book might let you see how the physics can be used for computation. You might at the end of it think that a quantum computer doesn't really have that many uses. Cracking codes and simulating molecules about sums it up - and this might well be true.

 

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Scratch Programming Playground

Author: Al Sweigart
Publisher: No Starch Press
Pages: 288
ISBN: 978-1593277628
Print: 1593277628
Kindle: B01LYJQVET
Audience: Kids and adults
Rating: 4.5
Reviewer: Lucy Black

A book that makes Scratch exciting. What more could you ask for?



Deep Learning: A Practitioner's Approach

Author: Josh Patterson and Adam Gibson
Publisher: O'Reilly
Pages: 536
ISBN: 978-1491914250
Print: 1491914254
Kindle: B074D5YF1D
Audience: Java engineers and practicing data scientists
Rating: 3
Reviewer: Mike James

AI is important and profitable, is this a good introduction?


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Last Updated ( Saturday, 23 November 2019 )