We study the complexity of computational problems from quantum physics. Typically, they are studied using the complexity class QMA (quantum counterpart of NP) but some natural computational problems appear to be slightly harder than QMA. We introduce new complexity classes consisting of problems that are solvable with a small number of queries to a QMA oracle and use these complexity classes to quantify the complexity of several natural computational problems (for example, the complexity of estimating the spectral gap of a Hamiltonian).
We study the complexity of computational problems from quantum physics. Typically, they are studied using the complexity class QMA (quantum counterpart of NP) but some natural computational problems appear to be slightly harder than QMA. We introduce new complexity classes consisting of problems that are solvable with a small number of queries to a QMA oracle and use these complexity classes to quantify the complexity of several natural computational problems (for example, the complexity of estimating the spectral gap of a Hamiltonian).
We study the complexity of computational problems from quantum physics. Typically, they are studied using the complexity class QMA (quantum counterpart of NP) but some natural computational problems appear to be slightly harder than QMA. We introduce new complexity classes consisting of problems that are solvable with a small number of queries to a QMA oracle and use these complexity classes to quantify the complexity of several natural computational problems (for example, the complexity of estimating the spectral gap of a Hamiltonian).
The problem of estimating the spectral gap of a local Hamiltonian is known to be contained in the class PQMA[log]: polynomial time with access to a logarithmic number of QMA queries. The problem was shown to be hard for PUQMA[log], a weaker class, under Turing reductions by Gharibian and Yirka [arXiv:1606.05626]. I give a brief proof that the Spectral Gap problem is QMA-hard under a many-one (Karp) reduction. Consequently, the problem is PQMA[log]-complete under truth-table reductions. It remains open to characterize the complexity of the Spectral Gap problem under many-one reductions. I conjecture that the problem belongs to a strict subclass of PQMA[log].
An important task in quantum physics is the estimation of local quantities for ground states of local Hamiltonians. Recently, [Ambainis, CCC 2014] defined the complexity class P^QMA[log], and motivated its study by showing that the physical task of estimating the expectation value of a local observable against the ground state of a local Hamiltonian is P^QMA[log]-complete. In this paper, we continue the study of P^QMA[log], obtaining the following results: (1) The P^QMA[log]-completeness result of [Ambainis, CCC 2014] above requires O(log(n))-local Hamiltonians and O(log(n))-local observables. Whether this could be improved to the more physically appealing O(1)-local setting was left as an open question. We resolve this question positively by showing that simulating even a single qubit measurement on ground states of 5-local Hamiltonians is P^QMA[log]-complete. (2) We formalize the complexity theoretic study of estimating two-point correlation functions against ground states, and show that this task is P^QMA[log]-complete. (3) P^QMA[log] is thought of as slightly harder than QMA. We give a formal justification of this intuition by exploiting the technique of hierarchical voting of [Beigel, Hemachandra, and Wechsung, SCT 1989] to show P^QMA[log] is in PP. This improves the known containment that QMA is in PP [Kitaev, Watrous, STOC 2000]. (4) A central theme of this work is the subtlety involved in the study of oracle classes in which the oracle solves a promise problem. In this vein, we identify a flaw in [Ambainis, CCC 2014] regarding a P^UQMA[log]-hardness proof for estimating spectral gaps of local Hamiltonians. By introducing a query validation technique, we build on [Ambainis, CCC 2014] to obtain P^UQMA[log]-hardness for estimating spectral gaps under polynomial-time Turing reductions.
This dissertation studies the interplay between quantum and classical computational resources through the lens of computational complexity theory. Part I considers low-energy states of quantum systems. We study the complexity of estimating ground- and excited-state energies of local Hamiltonians, given access to a guiding state promised to have non-negligible overlap with the relevant eigenspace. We formalise access models for such guiding states, examine their properties and relations, and study the problem for physically motivated Hamiltonians. We also study the task of obtaining approximate descriptions of ground states, given QMA-oracle access, in the setting of low-locality reduced density matrices. Part II focuses on quantum probabilistically checkable proof systems (QPCPs). We define a general class of QPCPs that allows adaptivity and multiple unentangled provers, and study its relationship to constant-gap local Hamiltonian problems via quantum reductions. Additionally, we investigate quantum–classical PCPs (QCPCPs), where a quantum verifier has either classical or quantum query access to a classical proof. Part III explores alternative complexity measures: unitary query complexity and sample complexity. For unitary query complexity, we develop a lower-bound technique based on unitary channel discrimination. In the context of sample complexity, we introduce and analyse a new sample-to-sample task, called complement sampling, and study the power of quantum computation with quantum samples over their classical counterparts.
Quantum computing involving physical systems with continuous degrees of freedom, such as the quantum states of light, has recently attracted significant interest. However, a well-defined quantum complexity theory for these bosonic computations over infinite-dimensional Hilbert spaces is missing. In this work, we lay foundations for such a research program. We introduce natural complexity classes and problems based on bosonic generalizations of BQP, the local Hamiltonian problem, and QMA. We uncover several relationships and subtle differences between standard Boolean classical and discrete variable quantum complexity classes and identify outstanding open problems. In particular: 1. We show that the power of quadratic (Gaussian) quantum dynamics is equivalent to the class BQL. More generally, we define classes of continuous-variable quantum polynomial time computations with a bounded probability of error based on higher-degree gates. Due to the infinite dimensional Hilbert space, it is not a priori clear whether a decidable upper bound can be obtained for these classes. We identify complete problems for these classes and demonstrate a BQP lower and EXPSPACE upper bound. We further show that the problem of computing expectation values of polynomial bosonic observables is in PSPACE. 2. We prove that the problem of deciding the boundedness of the spectrum of a bosonic Hamiltonian is co-NP-hard. Furthermore, we show that the problem of finding the minimum energy of a bosonic Hamiltonian critically depends on the non-Gaussian stellar rank of the family of energy-constrained states one optimizes over: for constant stellar rank, it is NP-complete; for polynomially-bounded rank, it is in QMA; for unbounded rank, it is undecidable.
In this paper we give an overview of the quantum computational complexity class QMA and a description of known QMA-complete problems to date. Such problems are believed to be difficult to solve, even with a quantum computer, but have the property that if a purported solution to the problem is given, a quantum computer would easily be able to verify whether it is correct. An attempt has been made to make this paper as self-contained as possible so that it can be accessible to computer scientists, physicists, mathematicians, and quantum chemists. Problems of interest to all of these professions can be found here.