An explosive development of quantum technologies since 1999 allowed the creation of arrays of natural and artificial quantum unit elements (viz. trapped ions and superconducting qubits), which maintain certain degree of quantum coherence and allow a degree of control over their quantum state. A natural application of such structures is towards simulating quantum systems, which are too big or too complex to allow a simulation with the means of classical computers. A digital quantum simulation promises a controlled accuracy, scalability and versatility, but it imposes practically as strict requirements on the hardware as a universal quantum computation. The other approach, analogue quantum simulation, is less demanding and thus more promising in short-to-medium term. It has already provided interesting results within the current experimental means and can be used as a stopgap approach as well as the means towards the perfecting of quantum technologies. Here I review the status of the field and discuss its prospects and the role it will play in the development of digital quantum simulation, universal quantum computing and, more broadly, quantum engineering.
An explosive development of quantum technologies since 1999 allowed the creation of arrays of natural and artificial quantum unit elements (viz. trapped ions and superconducting qubits), which maintain certain degree of quantum coherence and allow a degree of control over their quantum state. A natural application of such structures is towards simulating quantum systems, which are too big or too complex to allow a simulation with the means of classical computers. A digital quantum simulation promises a controlled accuracy, scalability and versatility, but it imposes practically as strict requirements on the hardware as a universal quantum computation. The other approach, analogue quantum simulation, is less demanding and thus more promising in short-to-medium term. It has already provided interesting results within the current experimental means and can be used as a stopgap approach as well as the means towards the perfecting of quantum technologies. Here I review the status of the field and discuss its prospects and the role it will play in the development of digital quantum simulation, universal quantum computing and, more broadly, quantum engineering.
Abstract The past few years have witnessed the concrete and fast spreading of quantum technologies for practical computation and simulation. In particular, quantum computing platforms based on either trapped ions or superconducting qubits have become available for simulations and benchmarking, with up to few tens of qubits that can be reliably initialized, controlled, and measured. The present Review aims at giving a comprehensive outlook on the state‐of‐the‐art capabilities offered from these near‐term noisy devices as universal quantum simulators, that is, programmable quantum computers potentially able to calculate the time evolution of many physical models. First, a pedagogic overview on the basic theoretical background pertaining digital quantum simulations is given, with a focus on hardware‐dependent mapping of spin‐type Hamiltonians into the corresponding quantum circuit as a key initial step toward simulating more complex models. Then, the main experimental achievements obtained in the last decade are reviewed, focusing on the digital quantum simulation of such spin models by employing two leading quantum architectures. Their performances are compared, and future challenges are outlined, also in view of prospective hybrid technologies, towards the ultimate goal of reaching the long‐sought quantum advantage for the simulation of complex many‐body models in the physical sciences.
Quantum simulation, as a practical application of noisy quantum computing, has aided the study of exotic quantum matters and the implementation of algorithms that outperform classical approaches. Superconducting qubits, one of the most promising candidates for realizing universal quantum computing, possess state-of-the-art features like easy integration of qubits, long coherence time, and high-fidelity single- and two-qubit gates. These characteristics have enabled applications of digital quantum simulation in the fields of physics, chemistry, and computer science. In this review, we first present the basic concepts of superconducting qubits, quantum gates, and digital quantum simulations. We also explore recent progress in digital quantum simulations using superconducting qubits, especially in relation to quantum chemistry, quantum matters, combinatorial optimization, and quantum machine learning. Finally, we address the current challenges of digital quantum simulation with superconducting qubits, and provide a perspective on the future of the field.
Quantum technologies went through an explosive development since the beginning of the century. The progress in the field of superconducting quantum structures was especially fast. As the result, the design and characterization of large quantum coherent structures became an engineering problem. We will discuss the current status of the emerging discipline of quantum engineering and possible ways of meeting its main challenge, the fundamental impossibility of an efficient modelling of a quantum system using classical means.
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.
Simulating quantum many-body systems is a key application for emerging quantum processors. While analog quantum simulation has already demonstrated quantum advantage, its digital counterpart has recently become the focus of intense research interest due to the availability of devices that aim to realize general-purpose quantum computers. In this perspective, we give a selective overview of the currently pursued approaches, review the advances in digital quantum simulation by comparing non-variational with variational approaches and identify hardware and algorithmic challenges. Based on this review, the question arises: What are the most promising problems that can be tackled with digital quantum simulation? We argue that problems of a qualitative nature are much more suitable for near-term devices then approaches aiming purely for a quantitative accuracy improvement.
Trapped ions offer long coherence times and high-fidelity, programmable quantum operations, making them a promising platform for quantum simulation of condensed matter systems, quantum dynamics, and problems related to high-energy physics. We review selected developments in trapped-ion qubits and architectures and discuss quantum simulation applications that utilize these emerging capabilities. This review emphasizes developments in digital (gate-based) quantum simulations that exploit trapped-ion hardware capabilities, such as flexible qubit connectivity, selective midcircuit measurement, and classical feedback, to simulate models with long-range interactions, explore nonunitary dynamics, compress simulations of states with limited entanglement, and reduce the circuit depths required to prepare or simulate long-range entangled states.