In the dissertation we study topics in quantum computation. First, we study the model of constant-depth quantum circuits. We study the family QNC0 of constant-depth quantum circuits, and the complexity classes associated with QNC0 circuits: EQNC0, NQNC0, and BQNC0e,d . We show certain containment results such as NQNC 0 = NQACC = NQP = coC =P and BQNC0e,d is in P for certain e and δ. Our results essentially refute a conjecture of Green et al. that NQACC ⊆ TC0. We also define and study complexity classes postEQP, postRQP, postNQP, and postBQNC0 We show containment results such as postBQNC0 = postBQP = PP and NQP = postRQP = postNQP.
Second, we study applications of quantum algorithms in computational group theory. We give results about quantum algorithms and reductions for group theoretic problems, concentrating mostly on solvable groups. We study two particular group theoretic problems—GROUP I NTERSECTION and DOUBLE COSET M EMBERSHIP. We show that these problems reduce to other group problems with known efficient quantum algorithms for many instances, yielding efficient quantum algorithms for GROUP INTERSECTION and DOUBLE COSET MEMBERSHIP on the same types of groups. Then we generalize and refine our results by introducing decision versions of the STABILIZER and ORBIT COSET problems, and showing that these new problems lie in between GROUP INTERSECTION and DOUBLE COSET MEMBERSHIP on the one hand, and the problem ORBIT SUPERPOSITION, on the other. We also show that GROUP INTERSECTION and D OUBLE COSET MEMBERSHIP have statistical zero knowledge proofs. Finally we give an alternative quantum algorithm for the problem of decomposing finite abelian groups.
In the dissertation we study topics in quantum computation. First, we study the model of constant-depth quantum circuits. We study the family QNC0 of constant-depth quantum circuits, and the complexity classes associated with QNC0 circuits: EQNC0, NQNC0, and BQNC0e,d . We show certain containment results such as NQNC 0 = NQACC = NQP = coC =P and BQNC0e,d is in P for certain e and δ. Our results essentially refute a conjecture of Green et al. that NQACC ⊆ TC0. We also define and study complexity classes postEQP, postRQP, postNQP, and postBQNC0 We show containment results such as postBQNC0 = postBQP = PP and NQP = postRQP = postNQP.
Second, we study applications of quantum algorithms in computational group theory. We give results about quantum algorithms and reductions for group theoretic problems, concentrating mostly on solvable groups. We study two particular group theoretic problems—GROUP I NTERSECTION and DOUBLE COSET M EMBERSHIP. We show that these problems reduce to other group problems with known efficient quantum algorithms for many instances, yielding efficient quantum algorithms for GROUP INTERSECTION and DOUBLE COSET MEMBERSHIP on the same types of groups. Then we generalize and refine our results by introducing decision versions of the STABILIZER and ORBIT COSET problems, and showing that these new problems lie in between GROUP INTERSECTION and DOUBLE COSET MEMBERSHIP on the one hand, and the problem ORBIT SUPERPOSITION, on the other. We also show that GROUP INTERSECTION and D OUBLE COSET MEMBERSHIP have statistical zero knowledge proofs. Finally we give an alternative quantum algorithm for the problem of decomposing finite abelian groups.
Quantum computation was proposed as an alternate computing process in the late-20th century, when classical computing models faced limitation in solving quantum mechanical problems. Major breakthroughs came in the 1990s, when quantum algorithms for integer factoring and black-box searching were invented that are faster than the best classical algorithms known even today. In this thesis, we look at quantum circuits with limited depth and size and analyse their power and limitations.
Computer Science is about the study of computational problems, many of which are motivated by real-world applications. We are interested as much in an actual method to solve a problem as in its unsolvability. In computational complexity theory we separate out the actual problem from the computing apparatus (e.g. a Turing machine, an AND-OR circuit) and analyse the hardness of the computation, due both to the intrinsic complexity of the problem and to the underlying model.
In this thesis, we consider quantum circuits built with a universal set of gates and show that non-constant depth is required to compute a particular function (parity) and other similar functions. The parity function, extensively studied previously, was shown to take non-constant depth for classical circuits too, thus providing an evidence of an inherent hardness in the function itself. On the other hand we show that the quantum circuit model is rich enough to build a universal circuit (one circuit that can simulate all circuits) that has roughly the same depth or size as the simulated circuit. We also consider a fault model in which some of the inputs to a gate might not be connected to the gate's output. We ask if we can detect the faulty inputs by testing the gate on different inputs. Our goal is to minimise the number of tests. We show that this is very hard for general gates but for certain gates it can be provably easier to detect faulty inputs. We even show that quantum algorithms can provably outperform classical algorithms for these gates. These results give us a sense of wherein lies the power of quantum computation and quantum circuits in particular.
Quantum computers were initially proposed to surpass the limitations of classical computers in simulating physical systems. Soon after, the field of quantum computing advanced through landmark discoveries of quantum algorithms, with some conjectured to provide exponential advantages over classical counterparts. These include Shor’s factoring algorithm, which has profound implications in cryptography. Additionally, moderate yet significant polynomial separations have further increased interest in the field. However, despite this progress, unconditional proofs confirming quantum superiority on the theoretical side remain elusive. At the same time, large, noise-resilient quantum computations on the experimental side, which could challenge the extended Church-Turing thesis by potentially breaking classical computational barriers, have yet to be achieved. Meanwhile, our understanding of the differences between classical and quantum mechanics has deepened. We now possess rigorous theoretical tools, such as Bell inequalities and nonlocal games, to describe behaviors unique to these theories. Moreover, the main loopholes for observing non-classical correlations have been closed experimentally, showing that correlations in the physical world exceed those predicted by classical mechanics. This thesis investigates computational complexity differences between quantum and classical models by studying shallow-depth circuits. The primary focus lies in identifying, elucidating, and proving computational quantum advantages. Additionally, the analysis delves into the bijection between these circuits and foundational non-local game constructions, exploring how quantum-classical deviations in multi-party correlation settings translate to computational advantages. A key question addressed is how to synthesize constant-depth quantum circuits for various problems to leverage quantum advantages. To this end, circuit synthesis techniques tailored to measurement-based quantum computation are developed, enabling simultaneously optimal quantum strategies for certain nonlocal games based on a particular bijection between this model and XOR non-local games. Building on this work, we confront a pivotal challenge: If a candidate quantum circuit potentially provides a computational advantage, how can we prove that no classical circuit surpasses it? This work presents new unconditional quantum-classical separations within shallow-depth settings, distinguishing for the first time constant-depth quantum circuits with one- and two-qubit gates from biased polynomial threshold circuits, which incorporate neural-network-type functionalities. These separations extend to prime-dimensional quantum systems, and we conjecture to have identified Razborov-Smolensky-type problems uniquely solvable by specific prime dimensions. The thesis also differentiates constant-depth quantum circuits with multi-qubit Toffoli gates from their classical counterparts, emphasizing the power of parallel quantum computation. Finally, verifying shallow-depth quantum computations is challenging due to conjectured exponential separations from classical computations, limiting correctness verification through simulation. While specific quantum algorithms within BQP have been addressed, we explore whether a quantum computer can reliably execute any instance from a fixed class of quantum circuits. Moving beyond heuristic-based solutions, we propose a benchmarking protocol that certifies, with exponentially high confidence, the execution of arbitrary circuits of specified dimensions, widths, and depths.
(Abridged abstract.) In this thesis we introduce new models of quantum computation to study the emergence of quantum speed-up in quantum computer algorithms. Our first contribution is a formalism of restricted quantum operations, named normalizer circuit formalism, based on algebraic extensions of the qubit Clifford gates (CNOT, Hadamard and π/4-phase gates): a normalizer circuit consists of quantum Fourier transforms (QFTs), automorphism gates and quadratic phase gates associated to a set G, which is either an abelian group or abelian hypergroup. Though Clifford circuits are efficiently classically simulable, we show that normalizer circuit models encompass Shor's celebrated factoring algorithm and the quantum algorithms for abelian Hidden Subgroup Problems. We develop classical-simulation techniques to characterize under which scenarios normalizer circuits provide quantum speed-ups. Finally, we devise new quantum algorithms for finding hidden hyperstructures. The results offer new insights into the source of quantum speed-ups for several algebraic problems. Our second contribution is an algebraic (group- and hypergroup-theoretic) framework for describing quantum many-body states and classically simulating quantum circuits. Our framework extends Gottesman's Pauli Stabilizer Formalism (PSF), wherein quantum states are written as joint eigenspaces of stabilizer groups of commuting Pauli operators: while the PSF is valid for qubit/qudit systems, our formalism can be applied to discrete- and continuous-variable systems, hybrid settings, and anyonic systems. These results enlarge the known families of quantum processes that can be efficiently classically simulated. This thesis also establishes a precise connection between Shor's quantum algorithm and the stabilizer formalism, revealing a common mathematical structure in several quantum speed-ups and error-correcting codes.
We study two group theoretic problems, GROUP INTERSECTION and DOUBLE COSET MEMBERSHIP, in the setting of black-box groups, where DOUBLE COSET MEMBERSHIP generalizes a set of problems, including GROUP MEMBERSHIP, GROUP FACTORIZATION, and COSET INTERSECTION. No polynomial-time classical algorithms are known for these problems. We show that for solvable groups, there exist efficient quantum algorithms for GROUP INTERSECTION if one of the underlying solvable groups has a smoothly solvable commutator subgroup, and for DOUBLE COSET MEMBERSHIP if one of the underlying solvable groups is smoothly solvable. We also study the decision versions of STABILIZER and ORBIT COSET, which generalizes GROUP INTERSECTION and DOUBLE COSET MEMBERSHIP, respectively. We show that they reduce to ORBIT COSET under certain conditions. Finally, we show that DOUBLE COSET MEMBERSHIP and DOUBLE COSET NONMEMBERSHIP have zero knowledge proof systems.
This project focused on upper and lower bounds for quantum computability using constant depth quantum circuits, and on the complexity theory of such circuits. It established significant differences between resource bounded quantum and classical computation models, particularly emphasizing new examples of where quantum circuits are more powerful than their classical counterparts. A second focus and outgrowth of this work was the creation of efficient quantum algorithms for specific problems and central combinatorial functions. Recent finding include upper bounds for the computational power of constant depth circuits composed of single qubit and CNOT gates, and lower bounds for the computational power of constant depth circuits with single qubit, CNOT and fanout gates. These results represent the power and the limits of small, possibly realizable quantum circuits. Also examined were bounds on computations with additional storage qubits (ancillae), and natural simple functions (realized by small depth circuits) which require ancillae for their computation.
The last decade witnessed a great surge of fruitful studies in the new paradigm of quantum computing. Remarkable progress has been made in all the areas including quantum algorithms, quantum complexity theory, quantum error-correcting code, quantum information theory, quantum cryptography and physical implementations of quantum computers. However, quantum algorithm design, probably the most important task in quantum computing, did not make as much progress as people expected. This thesis aims at both designing new quantum algorithms and studying why efficient quantum algorithms are so hard to design by proving many lower bounds on quantum query complexity for various problems.
We first review (and generalize) known techniques for designing quantum algorithms and for proving quantum lower bounds. Using these techniques, we then study the quantum query complexity for many problems, including some specific problems such as Graph Matching and other natural graph properties, the general tuple search, and local search. We also study the lowest possible quantum query complexity for a class of functions as a whole, such as graph properties, circular functions, and functions invariant of a transitive permutation group, where tight results are given in all these cases.
Finally for the quantum lower bounds techniques themselves, we study the main two techniques and show that they are incomparable in power. For the most widely used one, which has a lot of parameters to choose, we show limitations for it in terms of certificate complexity. This implies that we cannot use the method to prove better lower bounds for almost all known open problems in this area.