BQP PSPACE NP P PostBQP Computational Intractability As A Law of Physics Scott Aaronson University of Waterloo.

BQP

PSPACE

NP

P

PostBQP

Computational Intractability As A Law of Physics

Scott Aaronson

University of Waterloo

Things we never see…

Warp drive Perpetuum mobile

GOLDBACH CONJECTURE: TRUE

NEXT QUESTION

Übercomputer

Is the absence of these devices something physicists should think about?

YES YES

Goal of talk: Convince you to see the impossibility of übercomputers as a basic principle of physics

Problem: “Given a graph, is it connected?”

Each particular graph 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

Computer Science 101

NP: Nondeterministic Polynomial Time

37976595177176695379702491479374117272627593301950462688996367493665078453699421776635920409229841590432339850906962896040417072096197880513650802416494821602885927126968629464313047353426395204881920475456129163305093846968119683912232405433688051567862303785337149184281196967743805800830815442679903720933

Does

have a prime 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)?

P

NP

NP-complete

NP-hard

Graph connectivityPrimality testingMatrix determinantLinear programming…

Matrix permanentHalting problem…

Hamilton cycleSteiner treeGraph 3-coloringSatisfiabilityMaximum clique… Factoring

Graph isomorphism…

Does P=NP?The (literally) $1,000,000 question

Q: What if P=NP, and the algorithm takes n10000 steps?

A: Then we’d just change the question!

Q: Why is it so hard to prove PNP?

A: Mostly because algorithms can be so clever!

No.

What about quantum computers?

Shor 1994: BQP contains integer factoring

But factoring isn’t believed to be NP-complete.So the question remains: can quantum computers solve NP-complete problems efficiently?

Bennett et al. 1997: “Quantum magic” won’t be enough

If we throw away the problem structure, and just consider a “landscape” of 2n possible solutions, even a quantum computer needs ~2n/2 steps to find a correct solution

BQP: Bounded-Error Quantum Polynomial-Time

Quantum Adiabatic Algorithm (Farhi et al. 2000)

HiHamiltonian with easily-prepared

ground state

HfGround state encodes

solution to NP-complete problem

Problem: Eigenvalue gap can be exponentially small

Other Alleged Ways to Solve NP-complete Problems

Dip two glass plates with pegs between them into soapy water; let the soap bubbles form a minimum “Steiner tree” connecting the pegs (thereby solving a known NP-complete problem)

Protein folding: Can also get stuck at local optima (e.g., Mad Cow Disease)

DNA computers: Just massively parallel classical computers!

What would the world actually be like if we could solve NP-complete

problems efficiently?

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

Proof of Riemann

hypothesis with

10,000,000 symbols?

Shortest efficient

description of stock

market data?

• Implies, but is stronger than, PNP

• As falsifiable as it gets

• Consistent with currently-known physical theory

• Scientifically fruitful?

Alright, what can we say about this assumption?

The NP Hardness AssumptionThere is no physical means to solve NP complete problems in polynomial time.

Rest of talk: Show how complexity yields a new perspective on linearity of QM, anthropic postselection, closed timelike curves, and initial conditions

1. Nonlinear variants of the Schrödinger Equation

Abrams & Lloyd 1998: If quantum mechanics were nonlinear, one could exploit that to solve NP-complete problems in polynomial time

No solutions1 solution to NP-complete problem

Can take as an additional

argument for why QM is linear

2. Anthropic PrincipleFoolproof way to solve NP-complete problems in polynomial time (at least in the Many-Worlds Interpretation):

First guess a random solution. Then, if it’s wrong, kill yourself!

Technicality: If there are no solutions, you’re out of luck!Solution: With tiny probability don’t do anything. Then, if you find yourself in a universe where you didn’t do anything, there probably were no solutions, since otherwise you would’ve found one!

NP Hardness Assumption yields a nontrivial constraint on anthropic theorizing: no

use of the Anthropic Principle can be valid, if its validity

would give us a way to solve NP-complete problems in

polynomial time

What if we combine quantum computing with the Anthropic Principle?

I.e. perform a polynomial-time quantum computation, but where we can measure a qubit and assume the outcome will be |1

Leads to a new complexity class: PostBQP

(Postselected BQP)

Certainly PostBQP contains NP—but is it even bigger than that?

Some more animals from the complexity zoo…

PSPACE: Class of problems solvable with a polynomial amount of memory

PP: Class of problems of the form, “out of 2n possible solutions, are at least half of them correct?”

Adleman, DeMarrais, Huang 1998: BQP PP

Proof: Feynman path integral

Proof easily extends to show PostBQP PP

BQP

PP

NP

P

PostBQP

PSPACE A. 2004: PostBQP = PP

In other words, quantum postselection gives exactly the power of PP

Surprising part:

This characterization yields a half-page proof of a celebrated result of Beigel, Reingold, and Spielman, that PP is closed under intersection

Everyone’s first idea for a time travel computer: Do an arbitrarily long computation, then send the answer back in time to before you started

THIS DOES NOT WORK

Why not?

• Ignores the Grandfather Paradox

• Doesn’t take into account the computation you’ll have to do after getting the answer

3. Time Travel

Deutsch’s ModelA closed timelike curve (CTC) is a computational resource that, given an efficiently computable function f:{0,1}n{0,1}n, immediately finds a fixed point of f—that is, an x such that f(x)=x

Admittedly, not every f has a fixed point

But there’s always a distribution D such that f(D)=D

Probabilistic Resolution of the Grandfather Paradox- You’re born with ½ probability- If you’re born, you back and kill your grandfather- Hence you’re born with ½ probability

Let PCTC be the class of problems solvable in polynomial

time, if for any function f:{0,1}n{0,1}n described by a poly-size circuit, we can immediately get an x{0,1}n such that f(m)(x)=x for some m

Theorem: PCTC = PSPACE

Proof: PCTC PSPACE is easy

For PSPACE PCTC: Let sinit, sacc, and srej be the initial, accepting, and rejecting states of a PSPACE machine, and let (s) be the successor state of s. Then set

otherwise,:,

,0,:,

,1,:,

bsbsf

sbsf

sbsf

initrej

initacc

The only fixed point is an infinite loop, with b set to its “true” value

What if we perform a quantum computation around a CTC?

Let BQPCTC be the class of problems solvable in

quantum polynomial time, if for any superoperator E described by a quantum circuit, we can immediately get a mixed state such that E() =

Clearly PSPACE = PCTC BQPCTC

A., Watrous 2006: BQPCTC = PSPACE

If closed timelike curves exist, then quantum computers are no more powerful than classical ones

BQPCTC PSPACE: Proof Sketch

Furthermore, we can compute P exactly in PSPACE, using Csanky’s parallel algorithm for matrix inversion

111lim:

zMIzP

zSolution: Let

PMzzMIzMMPz

22

11lim

Then by Taylor expansion,

Hence P projects onto the fixed points of M

Let vec() be a “vectorization” of . We can reduce the problem to the following: given a 22n22n matrix M, prepare a state such that

vecvec M

4. Initial Conditions

Useful?

Normally we assume a quantum computer starts in an “all-0” state, |0…0. But what if much better initial states were created in the Big Bang, and have been sitting around ever since?

Leads to the concept of quantum advice…

|

Result #1: BQP/qpoly PostBQP/poly

“Any problem you can solve using short quantum advice, you can also solve using short classical advice, provided you’re willing to use exponentially more computation time to extract what the advice is telling you.”

Result #2: There exists an “oracle” relative to which NP BQP/qpoly

Limitations of Quantum AdviceA., 2004

Evidence that NP-complete problems are still hard for quantum computers in the presence of quantum advice

One can postulate bizarre, exponentially-hard-to-prepare initial states in Nature, without

violating the NP Hardness Assumption

Concluding Remarks

Prediction: NP Hardness Assumption will eventually be seen as analogous to Second Law of Thermodynamics or impossibility of superluminal signaling

COMPUTATIONAL COMPLEXITY

PHYSICSTHIS BRIDGE

ALREADY EXISTS

Open Question: What is polynomial time in quantum gravity? (First question: What is time in quantum gravity?)

Links to papers, etc.:www.scottaaronson.com