One of the most exciting potential applications of a quantum computer is the abilityto efficiently simulate quantum systems, a task that is out of the reach of even thelargest classical supercomputers. Such simulations require a quantum algorithm capableof efficiently representing and manipulating a quantum system, as well as a device withsufficient coherence to execute it. In this work, we describe experiments advancing bothof these goals. First, we discuss dephasing—currently a leading cause of decoherencein superconducting qubits—and present measurements accurately quantifying both low-and high-frequency phase noise sources. We then discuss two quantum algorithms forthe simulation of chemical Hamiltonians, and experimentally contrast their performance.These results show that with continuing improvement in quantum devices we may soonbe able to apply quantum computers to practical chemistry problems.
One of the most exciting potential applications of a quantum computer is the abilityto efficiently simulate quantum systems, a task that is out of the reach of even thelargest classical supercomputers. Such simulations require a quantum algorithm capableof efficiently representing and manipulating a quantum system, as well as a device withsufficient coherence to execute it. In this work, we describe experiments advancing bothof these goals. First, we discuss dephasing—currently a leading cause of decoherencein superconducting qubits—and present measurements accurately quantifying both low-and high-frequency phase noise sources. We then discuss two quantum algorithms forthe simulation of chemical Hamiltonians, and experimentally contrast their performance.These results show that with continuing improvement in quantum devices we may soonbe able to apply quantum computers to practical chemistry problems.
Quantum computing promises to revolutionize several scientific and technological domains through fundamentally new ways of processing information. Among its most compelling applications is digital quantum simulation, where quantum computers are used to replicate the behavior of other quantum systems. This could enable the study of problems that are otherwise intractable on classical computers, transforming fields such as quantum chemistry, condensed matter physics, and materials science. Despite this potential, realizations of practical quantum advantage for relevant problems are hindered by imperfections of current devices. This also affects quantum hardware based on superconducting circuits which is among the most advanced and scalable platforms. The envisaged long-term solution of fault-tolerant quantum computers that correct their own errors remains out of reach mainly due to the associated qubit number overhead. As a result, the field has developed strategies that combine quantum and classical resources, exploit hardware-native operations, and employ error mitigation techniques to extract meaningful results from noisy data. This doctoral thesis contributes to this broader effort by exploring methods for advancing quantum simulation across the full computational stack, including hardware-level innovations, refined techniques for noise modeling and error mitigation, and algorithmic improvements enabled by efficient measurement processing.
A quantum computer will potentially solve far-reaching problems which are currently intractable on any classical computer. Many technological obstacles have prevented the realization of a quantum computer, the main obstacle being decoherence, which is the loss of quantum information. Decoherence arises from the undesired interaction between qubits and their environment. Isolated qubits have better coherence but are more difficult to control. Superconducting qubits are a promising platform since their macroscopic size allows for easy control and coupling to other qubits. While the coherence of superconducting qubits has substantially improved over the past two decades, further improvements in coherence are required.We have repeatedly and reliably increased the coherence times of superconducting qubits. Currently decoherence in these devices is dominated by coupling to material defects. These defects are present in the dielectrics used to fabricate these devices or introduced during fabrication. Using simpler resonators as a testbed, we individually isolate, characterize, and then improve each step of the more complicated fabrication of superconducting qubits. We increased the quality factor of resonators by a factor of four by first identifying the surfaces and interfaces as a major source of loss and then by optimizing the substrate preparation. Furthermore, we measure and subsequently mitigate additional defect loss, which is dependent on the position of ground plane holes used to limit the loss from magnetic vortices. Implementing these improvements led to an increase of our qubit coherence times by more than an order of magnitude.The progress made in coherence while maintaining a high degree of connectivity and controllability has been directly used in more complex circuits. One such device is a fully connected three qubit ring with both tunable qubit frequencies and adjustable qubit-qubit couplings. The considerable level of control allows us to generate the quantum dynamics resulting from a collision between Na and He atoms by encoding the problem into a time-dependent multi-qubit interaction. We compute a scattering cross section by measuring the probability of exciting the Na atom over a wide range of collision parameters. The scattering cross-section shows that there is a velocity where the excitation probability is maximized, in agreement with scattering experiments.
During the last ten years, superconducting circuits have passed from being interesting physical devices to becoming contenders for near-future useful and scalable quantum information processing (QIP). Advanced quantum simulation experiments have been shown with up to nine qubits, while a demonstration of quantum supremacy with fifty qubits is anticipated in just a few years. Quantum supremacy means that the quantum system can no longer be simulated by the most powerful classical supercomputers. Integrated classical-quantum computing systems are already emerging that can be used for software development and experimentation, even via web interfaces. Therefore, the time is ripe for describing some of the recent development of superconducting devices, systems and applications. As such, the discussion of superconducting qubits and circuits is limited to devices that are proven useful for current or near future applications. Consequently, the centre of interest is the practical applications of QIP, such as computation and simulation in Physics and Chemistry.
Experimental progress is reviewed for superconducting phase qubit research at the University of California, Santa Barbara. The phase qubit has a potential advantage of scalability, based on the low impedance of the device and the ability to microfabricate complex “quantum integrated circuits”. Single and coupled qubit experiments, including qubits coupled to resonators, are reviewed along with a discussion of the strategy leading to these experiments. All currently known sources of qubit decoherence are summarized, including energy decay (T 1), dephasing (T 2), and measurement errors. A detailed description is given for our fabrication process and control electronics, which is directly scalable. With the demonstration of the basic operations needed for quantum computation, more complex algorithms are now within reach.
Accurate simulation of dynamic processes in molecules and reactions is among the most challenging problems in quantum chemistry. Quantum computers promise efficient chemical simulation, but the existing quantum algorithms require many logical qubits and gates, placing practical applications beyond existing technology. Here, we carry out the first quantum simulations of chemical dynamics by employing a more hardware-efficient encoding scheme that uses both qubits and bosonic degrees of freedom. Our trapped-ion device accurately simulates the dynamics of nonadiabatic chemical processes, which are among the most difficult problems in computational chemistry because they involve strong coupling between electronic and nuclear motions. We demonstrate the programmability and versatility of our approach by simulating the dynamics of three different molecules, as well as open-system dynamics in the condensed phase, all with the same quantum resources. Our approach requires orders of magnitude fewer resources than equivalent qubit-only quantum simulations, demonstrating the potential of using hybrid encoding schemes to accelerate quantum simulations of complex chemical processes, which could have applications in fields ranging from energy conversion and storage to biology and drug design.
Quantum simulation is a potentially powerful application of quantum computing, holding the promise to be able to emulate interesting quantum systems beyond the reach of classical computing methods. Despite such promising applications, and the increase in active research, there is little introductory literature or demonstrations of the topic at a graduate or undergraduate student level. This artificially raises the barrier to entry into the field which already has a limited workforce, both in academia and industry. Here we present an introduction to simulating quantum systems, starting with a chosen Hamiltonian, overviewing state preparation and evolution, and discussing measurement methods. We provide an example simulation by measuring the state dynamics of a tight-binding model with disorder by time evolution using the Suzuki-Trotter decomposition. Furthermore, error mitigation and noise reduction are essential to executing quantum algorithms on currently available noisy quantum computers. We discuss and demonstrate various error mitigation and circuit optimization techniques that significantly improve performance. All source code is freely available, and we encourage the reader to build upon it.