Nonpairwise multi-qubit interactions present a useful resource for quantum information processors. Their implementation would facilitate more efficient quantum simulations of moleculesand combinatorial optimization problems, and they could simplify error suppression and error correction schemes. Here we present a superconducting circuit architecture in which a coupling module mediates 2-local and 3-local interactions between three flux qubits by design. The system Hamiltonian is estimated via multi-qubit pulse sequences that implement Ramsey-type interferometry between all neighboring excitation manifolds in the system. The 3-local interaction is coherently tunable over several MHz via the coupler flux biases and can be turned off, which is important for applications in quantum annealing, analog quantum simulation, and gate-model quantum computation.
Multipartite entanglement is one of the core concepts in quantum information science with broad applications that span from condensed matter physics to quantum physics foundations tests.Although its most studied and tested forms encompass two-dimensional systems, current quantum platforms technically allow the manipulation of additional quantum levels. We report the first experimental demonstration of a high-dimensional multipartite entangled state in a superconducting quantum processor. We generate the three-qutrit Greenberger-Horne-Zeilinger state by designing the necessary pulses to perform high-dimensional quantum operations. We obtain the fidelity of 78±1%, proving the generation of a genuine three-partite and three-dimensional entangled state. To this date, only photonic devices have been able to create and manipulate these high-dimensional states. Our work demonstrates that another platform, superconducting systems, is ready to exploit high-dimensional physics phenomena and that a programmable quantum device accessed on the cloud can be used to design and execute experiments beyond binary quantum computation.
Superconducting circuits have emerged as a promising platform to build quantum processors. The challenge of designing a circuit is to compromise between realizing a set of performancemetrics and reducing circuit complexity and noise sensitivity. At the same time, one needs to explore a large design space, and computational approaches often yield long simulation times. Here we automate the circuit design task using SCILLA, a software for automated discovery of superconducting circuits. SCILLA performs a parallelized, closed-loop optimization to design circuit diagrams that match pre-defined properties such as spectral features and noise sensitivities. We employ it to discover 4-local couplers for superconducting flux qubits and identify a circuit that outperforms an existing proposal with similar circuit structure in terms of coupling strength and noise resilience for experimentally accessible parameters. This work demonstrates how automated discovery can facilitate the design of complex circuit architectures for quantum information processing.
The first post-classical computation will most probably be performed not on a universal quantum computer, but rather on a dedicated quantum hardware. A strong candidate for achievingthis is represented by the task of sampling from the output distribution of linear quantum optical networks. This problem, known as boson sampling, has recently been shown to be intractable for any classical computer, but it is naturally carried out by running the corresponding experiment. However, only small scale realizations of boson sampling experiments have been demonstrated to date. Their main limitation is related to the non-deterministic state preparation and inefficient measurement step. Here, we propose an alternative setup to implement boson sampling that is based on microwave photons and not on optical photons. The certified scalability of superconducting devices indicates that this direction is promising for a large-scale implementation of boson sampling and allows for more flexible features like arbitrary state preparation and efficient photon-number measurements.
With quantum computers being out of reach for now, quantum simulators are the alternative devices for efficient and more exact simulation of problems that are challenging on conventionalcomputers. Quantum simulators are classified into analog and digital, with the possibility of constructing „hybrid“ simulators by combining both techniques. In this paper, we focus on analog quantum simulators of open quantum systems and address the limit that they can beat classical computers. In particular, as an example, we discuss simulation of the chlorosome light-harvesting antenna from green sulfur bacteria with over 250 phonon modes coupled to each electronic state. Furthermore, we propose physical setups that can be used to reproduce the quantum dynamics of a standard and multiple-mode Holstein model. The proposed scheme is based on currently available technology of superconducting circuits consist of flux qubits and quantum oscillators.
Lattice protein folding models are a cornerstone of computational biophysics.
Although these models are a coarse grained representation, they provide useful
insight into the energylandscape of natural proteins. Finding low-energy
three-dimensional structures is an intractable problem even in the simplest
model, the Hydrophobic-Polar (HP) model. Exhaustive search of all possible
global minima is limited to sequences in the tens of amino acids. Description
of protein-like properties are more accurately described by generalized models,
such as the one proposed by Miyazawa and Jernigan (MJ), which explicitly take
into account the unique interactions among all 20 amino acids. There is
theoretical and experimental evidence of the advantage of solving classical
optimization problems using quantum annealing over its classical analogue
(simulated annealing). In this report, we present a benchmark implementation of
quantum annealing for a biophysical problem (six different experiments up to 81
superconducting quantum bits). Although the cases presented here can be solved
in a classical computer, we present the first implementation of lattice protein
folding on a quantum device under the Miyazawa-Jernigan model. This paves the
way towards studying optimization problems in biophysics and statistical
mechanics using quantum devices.
Open quantum system approaches are widely used in the description of
physical, chemical and biological systems. A famous example is electronic
excitation transfer in the initial stageof photosynthesis, where harvested
energy is transferred with remarkably high efficiency to a reaction center.
This transport is affected by the motion of a structured vibrational
environment, which makes simulations on a classical computer very demanding.
Here we propose an analog quantum simulator of complex open system dynamics
with a precisely engineered quantum environment. Our setup is based on
superconducting circuits, a well established technology. As an example, we
demonstrate that it is feasible to simulate exciton transport in the
Fenna-Matthews-Olson photosynthetic complex. Our approach allows for a
controllable single-molecule simulation and the investigation of energy
transfer pathways as well as non-Markovian noise-correlation effects.