Promise problem differences reshape quantum and classical oracle results

Promises should be taken seriously: On relativization with promise problems

Computational Complexity

Summary

The paper explores how computational models behave differently when given access to special helper tools called oracles, especially for promise problems — cases where inputs outside a certain range are not considered. The authors find that results proven for normal decision problems don't always hold for promise problems, which is important for understanding quantum versus classical computations. They also propose new ways to think about oracle access to better capture promise problem behavior and show that certain complexity classes behave unexpectedly under these assumptions. This helps clarify the boundaries of quantum computing power and related complexity theories.

What this means in practice

  • For quantum algorithm designers: Distinguish which oracle-based complexity results apply when designing algorithms relying on promise problems and quantum-classical comparisons.
  • For complexity theorists: Refine theoretical models in complexity theory by understanding new semantic notions of oracle queries for promise problems.

A theory result. No direct application yet.

Authors

David Miloschewsky, Supartha Podder, Dorian Rudolph

Abstract

Relativization is concerned with comparing computational models with black-box access to an oracle. For promise problems, black-box access is not canonical due to inputs outside of the promise being unconstrained. We study two semantics for such access. Under robust queries, a machine must correctly answer regardless of the completion of the problem,, while loose access requires that the internal choices of a machine do not change based on off-promise queries. Our first result separates the language and promise settings. Namely, we construct an oracle $O$ such that $\mathsf{P}^O = \mathsf{BQP}^O = \mathsf{AWPP}^O$, but $\mathsf{PromiseBQP}^O\not\subseteq\mathsf{PromiseP}^O_{\mathsf{/poly}}$. In particular, $\mathsf{BPP}^O = \mathsf{BQP}^O$, but $\mathsf{PromiseBQP}^O \neq \mathsf{PromiseBPP}^O$, showing that results for languages need not transfer to promises. Next, we use loose queries to strengthen the upper bound on the Quantum-Classical Polynomial Hierarchy from $\mathsf{P}^{\mathsf{PP}^{\mathsf{PP}}}$ to $\mathsf{QCPH} \subseteq \mathsf{BP\cdot PP} \subseteq \mathsf{PromiseBPP}^{\mathsf{PP}}$. The same proof also shows $\mathsf{PP}^\mathsf{PromiseBQP} = \mathsf{PP}$. Additionally, we show that $\mathsf{PromiseBQP}$, even when given quantum advice, is self-low under robust queries. Finally, we exhibit an obstruction to transferring language-level counting results to promise classes. Although $\mathsf{AWPP}$ and $\mathsf{APP}$ are low for $\mathsf{PP}$, a corresponding promise analogue would collapse the counting hierarchy as $\mathsf{GapP} \subseteq \mathsf{FP}^{\mathsf{PromiseAWPP}}$. This motivates the introduction of $\mathsf{PromisePostBQP^*}$, which restricts $\mathsf{PostBQP}$ to input-indepencent postselection. By showing that it is low for \PP, we obtain $\mathsf{PP}^{\mathsf{PromiseYQP^*}} = \mathsf{PP}$.