Quantum algorithms provide a potential strategy for solving computational problems that are intractable by classical means. Computing the topological invariants of topological matter is one central problem in research on quantum materials, and a variety of numerical approaches for this purpose have been developed. However, the complexity of quantum many-body Hamiltonians makes calculations of topological invariants challenging for interacting systems. Here, we present two quantum circuits for calculating Chern numbers of two-dimensional quantum matter on quantum computers. Both circuits combine a gate-based adiabatic time evolution over the discretized Brillouin zone with particular phase estimation techniques. The first algorithm uses many qubits, and we analyze it using a tensor-network simulator of quantum circuits. The second circuit uses fewer qubits, and we implement it experimentally on a quantum computer based on superconducting qubits. Our results establish a method for computing topological invariants with quantum circuits, taking a step towards characterizing interacting topological quantum matter using quantum computers. Published by the American Physical Society 2024
Quantum algorithms provide a potential strategy for solving computational problems that are intractable by classical means. Computing the topological invariants of topological matter is one central problem in research on quantum materials, and a variety of numerical approaches for this purpose have been developed. However, the complexity of quantum many-body Hamiltonians makes calculations of topological invariants challenging for interacting systems. Here, we present two quantum circuits for calculating Chern numbers of two-dimensional quantum matter on quantum computers. Both circuits combine a gate-based adiabatic time evolution over the discretized Brillouin zone with particular phase estimation techniques. The first algorithm uses many qubits, and we analyze it using a tensor-network simulator of quantum circuits. The second circuit uses fewer qubits, and we implement it experimentally on a quantum computer based on superconducting qubits. Our results establish a method for computing topological invariants with quantum circuits, taking a step towards characterizing interacting topological quantum matter using quantum computers. Published by the American Physical Society 2024
Topological quantum matter represents a flexible playground to engineer unconventional excitations. While non-interacting topological single-particle systems have been studied in detail, topology in quantum many-body systems remains an open problem. Specifically, in the quantum many-body limit, one of the challenges lies in the computational complexity of obtaining the many-body ground state and its many-body topological invariant. While algorithms to compute ground states with quantum computers have been heavily investigated, algorithms to compute topological invariants in a quantum computer are still under active development. Here we demonstrate a quantum circuit to compute the many-body topological invariant of a second-order topological quantum magnet encoded in qubits. Our algorithm relies on a quantum circuit adiabatic evolution in transverse paths in parameter space, and we uncover hidden topological invariants depending on the traversed path. Our work puts forward an algorithm to leverage quantum computers to characterize many-body topological quantum matter.
Abstract Topological insulators are exotic material that possess conducting surface states protected by the topology of the system. They can be classified in terms of their properties under discrete symmetries and are characterized by topological invariants. The latter has been measured experimentally for several models in one, two and three dimensions in both condensed matter and quantum simulation platforms. The recent progress in quantum simulation opens the road to the simulation of higher dimensional Hamiltonians and in particular of the 4D quantum Hall effect. These systems are characterized by the second Chern number, a topological invariant that appears in the quantization of the transverse conductivity for the non-linear response to both external magnetic and electric fields. This quantity cannot always be computed analytically and there is therefore a need of an algorithm to compute it numerically. In this work, we propose an efficient algorithm to compute the second Chern number in 4D systems. We construct the algorithm with the help of lattice gauge theory and discuss the convergence to the continuous gauge theory. We benchmark the algorithm on several relevant models, including the 4D Dirac Hamiltonian and the 4D quantum Hall effect and verify numerically its rapid convergence.
Topological phases of matter are characterized by global properties of quantum states beyond conventional local order parameters. The Chern number is a central invariant in this characterization, linking the geometry of quantum states to robust physical observables and making its determination key to understanding quantum matter. We construct a nearly optimal quantum algorithm for estimating the Chern number of a smooth Hamiltonian family over a two-dimensional parameter torus with a unique, gapped ground state, including interacting many-body systems. The algorithm transports and reuses two ground-state copies prepared at a single reference point and uses generalized quantum signal processing to coherently accumulate geometric phases. It achieves a Hamiltonian-oracle evolution time of O~(LxLy/Δmin3), where Lx,Ly bound the parameter derivatives of the Hamiltonian and Δmin is a known spectral-gap lower bound. We prove a matching worst-case oracle lower bound, even when the Chern number is promised to be zero or one, establishing optimality up to polylogarithmic factors. For local Hamiltonian families with an inverse-polynomial gap and a supplied guiding state, exact Chern-number computation is in FBQP and is BQP-hard, and merely deciding whether the Chern number is zero or one is already BQP-complete. These results establish how efficiently quantum computers can estimate a quantized topological invariant and provide evidence for quantum advantage in characterizing topological phases.
Quantum computers hold the promise of solving computational problems that are intractable for classical computers, by harnessing the principles of quantum mechanics. However, quantum computations are highly susceptible to noise and decoherence, which place strict limits on the size and depth of the circuits that can be reliably executed on current hardware. Topological quantum computing (TQC) has emerged as one of the promising approaches to building fault-tolerant quantum computers. The key idea is to store quantum information in the global properties of a physical system, making it naturally resilient to the local noise and errors that affect conventional qubits. This thesis focuses on synthetic topological quantum matter, the physical platform on which TQC is built, and investigates its electronic structure and topological properties. We study the conditions under which these systems enter a topological phase and host Majorana zero modes (MZMs), exotic zero-energy quasiparticles that appear at the boundaries of the system. MZMs are the key building block of TQC, as their quantum mechanical properties allow them to encode and process quantum information in a way that is protected from errors. We demonstrate the existence of MZMs in two canoni- cal topological systems, the Kitaev chain and the semiconducting-superconducting nanowire. To address the experimental challenge of detecting MZMs, we develop an optical spectroscopy technique based on excitonic interactions, which provides clear and measurable signatures of the topological phase. We also explore the variational quantum eigensolver as a quantum algorithmic approach to approximating the ground-state energy of the many-body spectrum of topological systems. Furthermore, we discuss the practical setups for topological quantum matter and simulate them through numerical analysis. Altogether, we present several theoretical and numerical methods that can be used for numerical simulations and practical purposes of detecting MZMs in topological quantum matter.
(English) In recent years, the evolution of quantum technologies has resulted in an unprecedented control over individual quantum particles and many-body systems. This remarkable progress has given rise to a new era, marked by the convergence of classical and quantum methodologies to investigate fundamental questions concerning the nature of quantum matter, improving our understanding of the role of entanglement in solid-state systems or the mechanisms behind high-energy physics. From analog quantum simulators to digital quantum computers, these advancements hold potential across diverse domains. This thesis explores the interplay between classical and quantum methods in understanding topological phases of matter. We concentrate on three distinct directions: non-conventional topological superconductors, interaction-induced topological phases in ultracold atom quantum simulators, and applications of variational quantum algorithms. Each trajectory relies on the combination of different techniques with the aim of understanding and characterizing topological phenomena in different settings. Exploring non-conventional topological superconductors involves extending the paradigmatic Kitaev chain model by incorporating additional terms in the Hamiltonian such as long-range interactions and quasi-periodic potentials. This investigation is relevant to better understand the impact of real-world conditions on the both the topological and localization properties of systems hosting non-local Majorana modes, which are promising candidates for topological quantum computation. In the realm of interacting systems, we explore the realization of interaction-induced topological phases in systems of ultracold atoms in optical lattices, both in one and two dimensions. The remarkable control and versatility of such platforms enable the simulation of both theoretical topological models and strongly correlated physics. Notably, the interplay between interactions and topology can give rise to intriguing phenomena, such as delocalized fractional charges and gapless topological phases,challenging existing intuition. We employ advanced numerical methods based on tensor networks to benchmark the experimental proposals that open the door to the realization and detection of novel many-body phases of matter, including topological quantum critical points and a higher-order topological Peierls insulator in Bose-Hubbard models with long-range interactions. Variational quantum algorithms, conversely, have the potential to efficiently tackle a wide range of problems, including ground state search, phase classification or accessing topological invariants. Despite current limitations in trainability and scalability, these hybrid classical-quantum algorithms provide practical insights into current quantum hardware capabilities and can inspire future architectures. We explore the application of variational quantum algorithms to shed light on topological phenomena, raising questions about their ability to discern topological phase transitions and compute topological invariants in situations where classical approaches fail. This thesis presents a comprehensive exploration of distinct approaches to topological quantum matter by leveraging quantum technologies and quantum-inspired classical algorithms. Our results not only advance our understanding of quantum systems but also pave the way for the realization and discovery of novel physics extending to quantum information processing, materials science, and beyond.
Nonlinear superconducting circuits are a leading candidate to implement quantum information tasks beyond the reach of classical processors. One such task, quantum simulation, involves using a controllable quantum system to study the dynamics of another. In this thesis, we present a series of experiments using small systems of superconducting circuits to perform various quantum tasks relevant to quantum simulation.In the first experiment, we design and build a circuit comprising three transmon qubits whose dynamics mirror those of interacting bosonic particles on a lattice, described by the Bose-Hubbard Hamiltonian. We verify the predictions of the Bose-Hubbard model for this system spectroscopically and then use time-domain measurements to study the decoherence processes affecting the qubits. Using a Raman process, we engineer artificial decay dynamics in the system which allow us to prepare and stabilize otherwise inaccessible states of the transmon array.The second experimental demonstration concerns topological quantum matter. Certain quantum systems are characterized by quantities known as topological invariants, which are robust to local perturbations. These topological invariants are challenging to measure in naturally-occurring systems. We engineer an artificial system, comprising a transmon qubit coupled to a high-Q cavity, capable of undergoing a protocol known as the quantum walk, which also exhibits topological invariants. By using particular non-classical state of the cavity, we modify the quantum walk protocol to make the topological invariant directly accessible.Finally, we implement a hybrid quantum-classical algorithm—known as the variational quantum eigensolver—in a two-transmon quantum processor. As a proof of principle demonstration, we compute the ground-state and low-lying excited state energies of the hydrogen molecule as a function of nuclear separation. We show that an extension of the basic algorithm, known as the quantum subspace expansion, allows for the mitigation of errors caused by decoherence processes affecting the quantum processor.