Quantum information science has emerged as one of the most promising fields in contemporary research, relying on both software and hardware innovations. This thesis looks for both algorithms with quantum features that provide advantages over classical algorithms, and better hardware platforms for experiments and quantum computing. The work spans theoretical studies in both algorithm and hardware design, including hybrid quantum-classical algorithms and the development of quantum information processing platforms. The algorithmic part has focused on the performance of a hybrid quantum algorithm - the Grover Quantum Approximate Optimization Algorithm (Grover QAOA) - designed for problems with multiple solutions. In practice, we find its potential for speedup in solution search and its ability to find all solutions. Furthermore, we propose a simplified protocol that reduces the classical complexity of optimizing the algorithm’s parameters, enhancing its practicality for future applications. Our implementation of Grover QAOA for multiple combinatorial optimization problems on trapped-ion quantum computers demonstrates that the algorithm can fulfill its fair-sampling advantage even on noisy devices. In the hardware part, we mainly explore how the motion of cold atoms can either be used to engineer interactions or lead to previously overlooked decoherence. The first hardware platform we discuss is trapped ions, where we focus on implementing individual addressing to natively simulate new types of many-body systems. Our proposal leverages the exceptional controllability of trapped ions to explore dynamical models such as topological pumping. The second hardware platform we study is Rydberg atom lattices, where we investigate the decoherence processes introduced by atomic motion during dynamics. Using the numerical tool of discrete truncated Wigner approximation, we simulate the coupled dynamics of electronic and motional degrees of freedom, demonstrating that atom motion induced by strong van der Waals interactions in Rydberg atoms can lead to significant decoherence in analog simulation experiments. We have also explored specialized topics involving other quantum hardware platforms. One area of study is the reduction of frequency crowding in superconducting circuit quantum chips. By properly designing the frequencies for each transmon qubit, we can improve the manufacturing yield of collision-free processors. Another area focuses on the SU(N) Fermi-Hubbard models on alkaline-earth-metal optical lattice platforms. We have obtained the phase diagram of unit-filling models with imbalanced spin flavors. This work aids future experiments in searching for potential ground states of the unit-filling SU(N) model.
Quantum information science has emerged as one of the most promising fields in contemporary research, relying on both software and hardware innovations. This thesis looks for both algorithms with quantum features that provide advantages over classical algorithms, and better hardware platforms for experiments and quantum computing. The work spans theoretical studies in both algorithm and hardware design, including hybrid quantum-classical algorithms and the development of quantum information processing platforms. The algorithmic part has focused on the performance of a hybrid quantum algorithm - the Grover Quantum Approximate Optimization Algorithm (Grover QAOA) - designed for problems with multiple solutions. In practice, we find its potential for speedup in solution search and its ability to find all solutions. Furthermore, we propose a simplified protocol that reduces the classical complexity of optimizing the algorithm’s parameters, enhancing its practicality for future applications. Our implementation of Grover QAOA for multiple combinatorial optimization problems on trapped-ion quantum computers demonstrates that the algorithm can fulfill its fair-sampling advantage even on noisy devices. In the hardware part, we mainly explore how the motion of cold atoms can either be used to engineer interactions or lead to previously overlooked decoherence. The first hardware platform we discuss is trapped ions, where we focus on implementing individual addressing to natively simulate new types of many-body systems. Our proposal leverages the exceptional controllability of trapped ions to explore dynamical models such as topological pumping. The second hardware platform we study is Rydberg atom lattices, where we investigate the decoherence processes introduced by atomic motion during dynamics. Using the numerical tool of discrete truncated Wigner approximation, we simulate the coupled dynamics of electronic and motional degrees of freedom, demonstrating that atom motion induced by strong van der Waals interactions in Rydberg atoms can lead to significant decoherence in analog simulation experiments. We have also explored specialized topics involving other quantum hardware platforms. One area of study is the reduction of frequency crowding in superconducting circuit quantum chips. By properly designing the frequencies for each transmon qubit, we can improve the manufacturing yield of collision-free processors. Another area focuses on the SU(N) Fermi-Hubbard models on alkaline-earth-metal optical lattice platforms. We have obtained the phase diagram of unit-filling models with imbalanced spin flavors. This work aids future experiments in searching for potential ground states of the unit-filling SU(N) model.
Quantum computers hold the potential of solving problems that are intractable using classical means. Yet, to date no quantum computer has actually solved a problem of general interest that could not have been solved otherwise. Bridging this gap from promised theoretical usefulness to practical relevance is an interdisciplinary challenge, requiring experimental progress, solutions of classical software challenges as well as advances in quantum algorithm design. It is these final two points in which this thesis aims to contribute. One of the most promising quantum computing architectures is based on trapping ions in surface-electrode ion-traps. In order to productively operate such trapped-ion quantum computers, we develop and benchmark a compiler that optimizes ion shuttling sequences in order to efficiently map abstract quantum circuits onto a physical trapped-ion chip. This is a necessary component of the infrastructure of a quantum computing setup, however it is alone not sufficient to execute arbitrary quantum algorithms. In particular, a very promising class of quantum algorithms are so-called hybrid quantum-classical algorithms which leverage the computational resources of both quantum and classical computers. To effectively implement such algorithms, a suitable software setup is necessary to allow for tight interplay between the two types of computers without wasting precious coherence time. To solve this challenge, we propose, implement and benchmark our setup for Interpreted Quantum-Classical Computations (IQCCs), demonstrating its feasibility for trapped-ion quantum computers. For the second part of this thesis we focus on the development of quantum algorithms that make use of this setup. As a first application, we investigate quantum simulations of gauge theories. Such theories are prevalent throughout modern physics and are characterized by local constraints that the dynamics are subject to. Errors in noisy simulations of such theories results in these constraints being violated and the simulations becoming unphysical. We show that this problem can be remedied by measuring gauge operators, decoding possible errors on a classical computer and actively correcting them, which reduces simulation errors. Additionally we interpret the scheme as a sympathetic cooling setup, which allows thermal control of the simulation. We finally turn to the task of preparing ground states of frustration-free Hamiltonians in quantum computers. Studying ground states of various systems is of paramount importance for solving optimization problems and understanding phenomena such as magnetism, superconductivity and superfluidity. We frame the ground-state preparation problem as an error correction problem, wherein energy is measured locally, measurements are decoded and corrections are applied to reduce the energy. In physically relevant examples we show up to exponentially improved runtimes over previous, similar algorithms and give a general run-time bound in terms of the Hamiltonian gap.
In recent decades, the rapid development of quantum technologies has led to a new era of programmable platforms, enabling the realizations of quantum simulation and quantum computation. This dissertation is motivated by recent experimental progress on controlling individual quantum degrees of freedom in systems such as trapped ions and Rydberg atom arrays. By tailoring the interactions in these quantum systems, we study analog quantum simulations of various physical phenomena, including non-equilibrium quantum dynamics and nontrivial topological physics. In the first part of the dissertation, we study slow quantum many-body dynamics in trapped-ion systems and Rydberg atom arrays. We first show that either the long-range interactions or an additional symmetry-breaking field can give rise to a confining potential. Such a potential can couple domain wall quasiparticles into mesonic or baryonic bound states. These confined quasiparticles strongly suppress the quantum information dynamics and lead to slow thermalization. In thelimit of strict domain-wall confinement, the full Hilbert space is fragmented into exponentially many disconnected subspaces. Furthermore, we demonstrate that thermalization can be halted by quantum engineering a uniformly increasing field in the trapped-ion quantum simulator. The second part of the dissertation focuses on topologically relevant phenomena in quantum simulators. We first study the effect of experimentally relevant disorder in 2D Rydberg atom arrays. We find that there are three distinct localization regimes due to the presence of nontrivial topological bands. We further study the non-equilibrium dynamics of Abelian anyons in a one-dimensional system. We show that the interplay of anyonic statistics and interactions can give rise to spatially asymmetric quantum dynamics. Finally, we use Nielsen’s geometric approach to quantify circuit complexity in topological models. We find that the circuit complexities of ground states and non-equilibrium steady states both exhibit nonanalytical behavior at topological transition points.
The creation and coherent control of systems of many strongly-interacting quantum particles represents one of the most important challenges in quantum science and technology. Devices capable of performing such a task have applications ranging from sensing and simulation, to communications and computation. The past few decades have seen remarkable progress in the development of different platforms to address the challenges of isolating and controlling individual quantum objects and increasing the number of interacting elements. This thesis presents a novel platform using arrays of individually controlled neutral atoms in optical tweezers which enables high-fidelity control of large systems of strongly interacting particles. Using real-time imaging and feedback, we initialize the positions of hundreds of atoms in arbitrary one- and two-dimensional geometries. By coupling the internal state of the atoms to highly excited Rydberg states, we are able to introduce spatially-dependent interactions to the system. Combining the remarkable coherence properties of isolated neutral atoms with strong Rydberg interactions, we study complex spin Hamiltonians in regimes beyond classical simulability. In the context of quantum simulation, we use this platform to study the phase diagram of regular arrays, including the critical properties of some of the associated quantum phase transitions. Additionally, we report on the discovery of special slowly-thermalizing states known as quantum many-body scars, which are then used as a starting point to stabilize many-body dynamics across the Hilbert space. Through the addition of specialized local controls, we demonstrate the ability to generate large N-partite entangled states with up to 20 atoms, as well as the ability to implement quantum logic gates. We combine quantum simulation with quantum information processing by preparing states with signatures of quantum spin liquids, which may be developed as topologically protected qubits. Lastly, we explore the potential applications of this platform to classical combinatorial optimization problems by approximating the Maximum Independent Set of different graphs.
Universal digital quantum computers are able to approximate any Hamiltonian evolution as a digital quantum circuit consisting of discrete time steps. Strongly interacting physics models, for example in high-energy physics or materials science, make this a challenging task for near-term devices as they place a high demand on the quantum resources required [1]. One alternative is analog quantum simulation where the native evolution of a quantum system can be tailored to mimic that of the model of interest. While more efficient at specific problems, there are limits on the types of evolution available and on the observables that can be measured. In this conference paper we present first results towards unifying these two concepts in a trapped-ion experiment. Trapped atomic ions are one of the most advanced experimental platforms for both analog quantum simulation and digital quantum computing. Typically, the internal spin degrees of freedom are used qubits or for the simulation of spin models. The harmonic oscillator modes given by the motion of the ions in the trap are only employed transiently to create quantum gates or spin-spin interactions. However, these motional modes constitute a large Hilbert space themselves and present a bosonic degree of freedom, which is costly to model with qubits. Many systems of interest, for example Lattice gauge theories, require both spin and boson degrees of freedom. It was recently shown that they can be encoded more efficiently using the harmonic oscillator modes directly [2].
Quantum computing represents an exciting frontier in the realm of information processing; it is a promising technology that may provide future advances in a wide range of fields, from quantum chemistry to optimization problems. This thesis discusses experimental results for several quantum algorithms performed on a programmable quantum computer consisting of a linear chain of five or seven trapped 171Yb+ atomic clock ions with long coherence times and high gate fidelities. We execute modular one- and two-qubit computation gates through Raman transitions driven by a beat note between counter-propagating beams from a pulsed laser. The system's individual addressing capability provides arbitrary single-qubit rotations as well as all possible two-qubit entangling gates, which are implemented using a pulse-segmentation scheme. The quantum computer can be programmed from a high-level interface to execute arbitrary quantum circuits, and comes with a toolbox of many important composite gates and quantum subroutines. We present experimental results for a complete three-qubit Grover quantum search algorithm, a hallmark application of a quantum computer with a well-known speedup over classical searches of an unsorted database, and report better-than-classical performance. The algorithm is performed for all 8 possible single-result oracles and all 28 possible two-result oracles. All quantum solutions are shown to outperform their classical counterparts. Performing parallel operations will be a powerful capability as deeper circuits on larger, more complex quantum computers present new challenges. Here, we perform a pair of 2-qubit gates simultaneously in a single chain of trapped ions. We employ a pre-calculated pulse shaping scheme that modulates the phase and amplitude of the Raman transitions to drive programmable high-fidelity 2-qubit entangling gates in parallel by coupling to the collective modes of motion of the ion chain. Ensuring the operation yields only spin-spin interactions between the desired pairs, with neither residual spin-motion entanglement nor crosstalk spin-spin entanglement, is a nonlinear constraint problem, and pulse solutions are found using optimization techniques. As an application, we demonstrate the quantum full adder using a depth-4 circuit requiring the use of parallel 2-qubit operations.
Advances in the programmability of quantum many-body systems have stimulated the development of novel computational and scientific applications. In this dissertation, we address a few fundamental and practical questions on using programmable quantum systems for analog quantum simulations and quantum optimization algorithms. We also design concrete experimental schemes to engineer the many-body dynamics that can be harnessed for these and other applications. On analog quantum simulations, we initiate the rigorous study of the physical resource complexity required to simulate a quantum Hamiltonian by another whose underlying interaction graph is simpler. In particular, we show a surprising result that unlike the classical setting, reducing the graph degree to a constant is impossible in general unless the interaction energy diverges with system size n. Instead, we develop a new construction where such degree-reduction becomes possible using O(poly(n)) interaction energy, which is exponentially better than what was known previously. On quantum optimization, we investigate the properties of a general-purpose Quantum Approximate Optimization Algorithm (QAOA). We develop a parameter-optimization procedure for the QAOA that is exponentially more efficient than standard strategies and reveal a mechanism of the algorithm to exploit non-adiabatic operations. We also analyze the typical-case performance of the QAOA on the Sherrington-Kirkpatrick spin glass problem and find that it can outperform the classical semi-definite programming algorithm. Lastly, we develop efficient and robust methods to experimentally implement many-body dynamics for algorithmic and physics applications. We design several experimental implementations based on neutral atoms with Rydberg interactions, which can be applied to quantum optimization algorithms, preparation of entangled many-body states, and engineering novel interactions between photons.