Algorithms for quantum computers. Andrew Childs Department of Combinatorics & Optimization and Institute for Quantum Computing University of Waterloo

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Algorithms for quantum computers Andrew Childs Department of Combinatorics & Optimization and Institute for Quantum Computing University of Waterloo

What is a computer? A means for performing calculations by following a sequence of instructions.

Turing machines In 1936, Alan Turing formulated what has become the standard mathematical model of computation. The Turing machine is a mathematical abstraction of a concrete physical process.

The Church-Turing thesis Church-Turing Thesis Any calculation that can be performed by mechanical means can be performed by a Turing machine. Consistent with everything we know about physics. What about efficiency? Strong Church-Turing Thesis Any calculation that can be performed efficiently by mechanical means can be performed efficiently by a Turing machine.

Challenging the strong Church-Turing thesis Quantum mechanics seems to be hard for computers to simulate. A system of n quantum particles is described by 2 n complex numbers. We don t know how to predict the outcomes of experiments using less than an exponential amount of computation. As far as I can tell, you can simulate this with a quantum system, with quantum computer elements. It s not a Turing machine, but a machine of a different kind. Do quantum systems naturally perform exponentially hard calculations? Can we harness this power?

A simple experiment 50% detectors laser 50% 50/50 beamsplitter (half-silvered mirror)

Interferometer 50%? 50%? laser

Interferometer 0% 100% laser

Phase shifts sin 2 ϕ 1 ϕ 0 2 cos 2 ϕ 1 ϕ 0 2 φ0 laser φ1

Four possible functions: Deutsch s problem Given: A function f: {0,1} {0,1} (As a black box: You can call the function f, but you can t read its source code.) Task: Determine whether f is constant. x f1(x) x f2(x) 0 0 0 1 1 0 1 1 constant x f3(x) x f4(x) 0 0 0 1 1 1 1 0 not constant Classically, two function calls are required to solve this problem.

Deutsch s algorithm f is not constant f is constant π f(0) laser π f(1)

Factoring integers Factoring integers is believed to be computationally difficult. 3107418240490043721350750035888567930037346022842 7275457201619488232064405180815045563468296717232 8678243791627283803341547107310850191954852900733 7724822783525742386454014691736602477652346609 = 1634733645809253848443133883865090859841783670033 092312181110852389333100104508151212118167511579 1900871281664822113126851573935413975471896789968 515493666638539088027103802104498957191261465571 The security of modern electronic commerce relies on this assumption! In 1994, Peter Shor showed that quantum computers can efficiently factor integers. In a nutshell: Quantum computers can efficiently detect periodicity. The periodicity of the powers of a number modulo N is closely related to the prime factorization of N.

Building a quantum computer optics trapped ions quantum dots superconducting circuits

Experimental progress

What are quantum computers good for? Factoring integers Other hard number theory problems (Pell s equation, counting points on curves,...) Simulating quantum mechanics Search Approximating topological invariants

A two-player game Consider a two-player game between Andrea and Orlando where Andrea goes first players alternate moves each player has two possible moves during their turn ( left or right ) there are a total of k turns the winner after any given sequence of moves (n = 2 k possibilities) is given by a function f: {L, R} k {0, 1} Problem: How many times must we call the function f to decide whether Andrea has a winning move?

Game trees Evaluate a tree of AND and OR gates: Andrea wins if she can make any move that gives 0 i.e., she only loses if all of her moves give 1 (AND) Orlando wins if he can make any move that gives 1 (OR) Example (k = 4): 1 and 1 1 or or 0 1 1 0 and and and and 1 0 1 1 1 1 0 0 or or or or or or or or 0 1 0 0 1 1 1 0 1 0 1 1 0 0 0 0

Classical algorithms Deterministic strategy: May have to query all n = 2 k leaves Randomized strategy: Pick a random move (L or R) Recursively evaluate the corresponding subtree If the result determines the evaluation (AND(0, x) = 0, OR(1, y) = 1) then return the appropriate value Otherwise, evaluate the other subtree to determine the value Exercise: The expected number of leaves queried is about k 1+ 33 = n 0.753... 4 In fact, this is optimal!

Explore the game tree in quantum superposition ( quantum walk ) A quantum algorithm nand nand nand nand nand nand nand nand nand nand nand nand nand nand nand 0 1 0 0 1 1 1 0 1 0 1 1 0 0 0 0 Phase depends on the value of the game This algorithm evaluates the game with arbitrarily good success probability in only about n 0.5 queries!

The future of quantum computing Experimental challenge: robust control of quantum systems How can we build a scalable quantum computer? Theoretical challenge: programming quantum computers How can we discover new fast quantum algorithms?