### A breakthrough on QMA(2)?

Friday, October 30th, 2015Last night, Martin Schwarz posted a preprint to the arXiv that claims to show the new complexity class containment QMA(2) ⊆ EXP. (See also his brief blog post about this result.) Here QMA(2) means Quantum Merlin-Arthur with two Merlins—i.e., the set of languages for which a “yes” answer can be witnessed by two unentangled quantum states, |ψ〉⊗|φ〉, on polynomially many qubits each, which are checked by a polynomial-time quantum algorithm—while EXP means deterministic exponential time. Previously, the best upper bound we had was the trivial QMA(2) ⊆ NEXP (Nondeterministic Exponential Time), which comes from guessing exponential-size classical descriptions of the two quantum proofs.

Whether QMA(2) is contained in EXP is a problem that had fascinated me for a decade. With Salman Beigi, Andy Drucker, Bill Fefferman, and Peter Shor, we discussed this problem in our 2008 paper The Power of Unentanglement. That paper (with an additional ingredient supplied by Harrow and Montanaro) shows how to prove that a 3SAT instance of size n is satisfiable, using two unentangled quantum proofs with only Õ(√n) qubits each. This implies that searching over all n-qubit unentangled proofs must take at least exp(n^{2}) time, unless 3SAT is solvable in 2^{o(n)} time (i.e., unless the Exponential Time Hypothesis is false). However, since EXP is defined as the set of problems solvable in 2^{p(n)} time, for *any* polynomial p, this is no barrier to QMA(2) ⊆ EXP being true—it merely constrains the possible techniques that could prove such a containment.

In trying to prove QMA(2) ⊆ EXP, the fundamental difficulty is that you need to optimize over *unentangled* quantum states only. That might sound easier than optimizing over all states (including the entangled ones), but ironically, it’s harder! The reason why it’s harder is that optimizing over all quantum states (say, to find the one that’s accepted by some measurement with the maximum probability) is a convex optimization problem: in fact, it boils down to finding the principal eigenvector of a Hermitian matrix. By contrast, optimizing over only the separable states is a non-convex optimization problem, which is NP-hard to solve exactly (treating the dimension of the Hilbert space as the input size n)—meaning that the question shifts to what sorts of approximations are possible.

Last week, I had the pleasure of speaking with Martin in person, when I visited Vienna, Austria to give a public lecture at the wonderful new research institute IST. Martin was then ironing out some final wrinkles in his proof, and I got to watch him in action—in particular, to see the care and detachment with which he examined the possibility that his proof might imply too much (e.g., that NP-complete problems are solvable in quasipolynomial time). Fortunately, his proof turned out not to imply anything of the kind.

The reason why it didn’t is directly related to the most striking feature of Martin’s proof—namely, that it’s *non-relativizing, *leaving completely open the question of whether QMA(2)^{A} ⊆ EXP^{A} relative to all oracles A. To explain how this is possible requires saying a bit about how the proof works. The obvious way to prove QMA(2) ⊆ EXP—what I had assumed from the beginning was the *only* realistic way—would be to give a quasipolynomial-time approximation algorithm for the so-called *Best Separable State* or BSS problem. The BSS problem, as defined in this paper by Russell Impagliazzo, Dana Moshkovitz, and myself (see also this one by Barak et al.), is as follows: you’re given as input an n^{2}×n^{2} Hermitian matrix A, with all its eigenvalues in [0,1]. Your goal is to find length-n unit vectors, u and w, that maximize

(u^{T}⊗w^{T})A(u⊗w),

to within an additive error of ±ε, for some constant ε.

Of course, if we just asked for a length-n^{2} unit vector v that maximized v^{T}Av, we’d be asking for the principal eigenvector of A, which is easy to find in polynomial time. By contrast, from the ABDFS and Harrow-Montanaro results, it follows that the BSS problem, for constant ε, cannot be solved in poly(n) time, unless 3SAT is solvable in 2^{o(n)} time. But this still leaves the possibility that BSS is solvable in n^{log(n)} time—and that possibility would immediately imply QMA(2) ⊆ EXP. So, as I and others saw it, the real challenge here was to find a quasipolynomial-time approximation algorithm for BSS—something that remained elusive, although Brandao-Christandl-Yard made partial progress towards it.

But now Martin comes along, and proves QMA(2) ⊆ EXP in a way that sidesteps the BSS problem. The way he does it is by using the fact that, if a problem is in QMA(2), then we don’t merely know a Hermitian operator A corresponding to the measurement of |ψ〉⊗|φ〉: rather, we know an actual polynomial-size sequence of quantum gates that get multiplied together to produce A. Using that fact, Chailloux and Sattath showed that a natural variant of the QMA-complete Local Hamiltonians problem, which they call Separable Sparse Hamiltonians, is complete for QMA(2). Thus, it suffices for Martin to show how to solve the Separable Sparse Hamiltonians problem in singly-exponential time. This he does by using perturbation theory gadgets to reduce Separable Sparse Hamiltonians to Separable *Local* Hamiltonians with an exponentially-small promise gap, and then using a result of Shi and Wu to solve the latter problem in singly-exponential time. All in all, given the significance of the advance, Martin’s paper is remarkably short; a surprising amount of it boils down to deeply understanding some not-especially-well-known results that were already in the literature.

One obvious problem left open is whether the full BSS problem—rather than just the special case of it corresponding to QMA(2)—is solvable in quasipolynomial time after all. A second obvious problem is whether the containment QMA(2) ⊆ EXP can be improved to QMA(2) ⊆ PSPACE, or even (say) QMA(2) ⊆ PP. (By comparison, note that QMA ⊆ PP, by a result of Kitaev and Watrous.)

**Update (Nov. 10):** I thought I should let people know that a serious concern has been raised by an expert about the correctness of the proof—and in particular, about the use of perturbation theory gadgets. Martin tells me that he’s working on a fix, and I very much hope he’ll succeed, but not much to do for now except let the scientific process trundle along (which doesn’t happen at blog-speed).