What Google Won’t Find: The Ultimate Physical Limits of Search Scott Aaronson University of Waterloo.
Download ReportTranscript What Google Won’t Find: The Ultimate Physical Limits of Search Scott Aaronson University of Waterloo.
What Google Won’t Find: The Ultimate Physical Limits of Search Scott Aaronson University of Waterloo Why Am I Speaking Here? “Is Google God?” —Thomas Friedman, NYT, 6/29/2003 My field—theoretical computer science—is directly concerned with the question of how to distinguish God from mortal impostors. CS Theory in One Slide Problem: “Given the Internet, are at least 50% of web pages all reachable from one another?” Each particular Internet is an instance The size of the instance, n, is the number of bits needed to specify it An algorithm is polynomial-time if it uses at most knc steps, for some constants k,c P is the class of all problems that have polynomial-time algorithms NP: Nondeterministic Polynomial Time Does 37976595177176695379702491479374117272627593 30195046268899636749366507845369942177663592 04092298415904323398509069628960404170720961 97880513650802416494821602885927126968629464 31304735342639520488192047545612916330509384 69681196839122324054336880515678623037853371 49184281196967743805800830815442679903720933 have a factor ending in 7? NP-hard: If you can solve it, you can solve everything in NP NP-complete: NP-hard and in NP Is there a Hamilton cycle (tour that visits each vertex exactly once)? NP-hard Hamilton cycle Graph 3-coloring Satisfiability Maximum clique … NPcomplete NP Graph connectivity Primality testing Linear programming … P Halting problem Counting problems … Factoring Graph isomorphism … Audience Exam Does P=NP? Answer: No. Extra credit: Prove it. (You’ll win at least $1,000,000 if you do) What could we do if we could solve NP-complete problems? If there actually were a machine with [running time] ~Kn (or even only with ~Kn2), this would have consequences of the greatest magnitude. —Gödel to von Neumann, 1956 Then why is it so hard to prove PNP? Algorithms can be very clever Gödel/Turing-style diagonalization arguments don’t seem powerful enough Combinatorial arguments face the “Razborov-Rudich barrier” But maybe there’s some physical system that solves an NP-complete problem just by “relaxing” to its lowest energy state? - Dip two glass plates with pegs between them into soapy water - Let the soap bubbles form a minimum Steiner tree connecting the pegs Other Physical Systems Spin glasses Folding proteins ... Well-known to admit “metastable” states DNA computers: Just highly parallel ordinary computers It’s Quantum Time If an object can be in two states |0 or |1, then it can also be in a superposition |0 + |1 Here and are complex amplitudes satisfying ||2+||2=1 If we observe, we see |0 with probability ||2 |1 with probability ||2 Also, the object collapses to whichever outcome we see 1 0 1 2 0 To modify a state n i 1 i i we can multiply the vector of amplitudes by a unitary matrix—one that preserves n i 1 2 i 1 0 1 1 2 1 2 1 1 1 2 12 20 1 01 11 2 2 2 2 1 0 1 2 We’re seeing interference between positive and negative amplitudes—the source of all “quantum weirdness” 0 Quantum Computing A quantum state of n “qubits” takes 2n complex numbers to describe: x0,1 x x n The goal of quantum computing is to exploit this exponentiality in Nature. Shor 1994: QuantumInteresting computers can factor integers in polynomial time But what about NP-complete problems? Bennett, Bernstein, Brassard, Vazirani 1994: “Quantum magic” won’t be enough Even a quantum computer would need ~2n/2 queries to search an unsorted array of size 2n for a single “marked” item “Relativity Computing” DONE Analog Computing Do the first step of a computation in 1 sec, the second in ½ sec, the third in ¼ sec, … Possible in “Malament-Hogarth spacetimes,” which have naked singularities Problem: The Planck scale (10-33 cm, 10-43 sec) seems to impose a fundamental limit! Time Travel Computing Naïve idea: Do the first step of a computation, then go back in time and do the next step, etc. Problem: Grandfather paradoxes Resolution (Deutsch 1991): Use probability or quantum theory. E.g. you’re born with ½ probability, and if you’re born you go back and kill your grandfather, ergo you’re born with ½ probability, etc. Immediately suggests a model of computation, which can be shown to be exactly as powerful as the class PSPACE (A. 2005) Quantum Gravity Freedman, Kitaev, Wang 2000: “Topological quantum field theories,” a particular class of (2+1)-dimensional quantum gravity theories, yield no more power than ordinary quantum computers String theory? Loop quantum gravity? It’d help if the physicists themselves understood these things better! “Anthropic Computing” Guess a solution to an NP-complete problem. If it’s wrong, kill yourself. Suppose you could kill yourself in all universes where a quantum computer fails, then condition on remaining alive. What’s the class of problems you could then solve in polynomial time? A. 2005: It’s exactly the classical complexity class PP (Probabilistic Polynomial-Time), which is believed to be strictly larger than NP Second Law of Thermodynamics Proposed Counterexamples No Superluminal Signalling Proposed Counterexamples Intractability of NP-complete problems Proposed Counterexamples Concluding Remark I know this talk seemed pessimistic… But I’m an optimist