Artificial Spins Research Articles

Parametric Frequency Divider Based Ising Machines.

We report on a new class of Ising machines (IMs) that rely on coupled parametric frequency dividers (PFDs) as macroscopic artificial spins. Unlike the IM counterparts based on subharmonic-injection locking (SHIL), PFD IMs do not require strong injected continuous-wave signals or applied dc voltages. Therefore, they show a significantly lower power consumption per spin compared to SHIL-based IMs, making it feasible to accurately solve large-scale combinatorial optimization problems that are hard or even impossible to solve by using the current von Neumann computing architectures. Furthermore, using high quality factor resonators in the PFD design makes PFD IMs able to exhibit a nanowatt-level power per spin. Also, it remarkably allows a speedup of the phase synchronization among the PFDs, resulting in shorter time to solution and lower energy to solution despite the resonators' longer relaxation time. As a proof of concept, a 4-node PFD IM has been demonstrated. This IM correctly solves a set of Max-Cut problems while consuming just 600 nanowatts per spin. This power consumption is 2 orders of magnitude lower than the power per spin of state-of-the-art SHIL-based IMs operating at the same frequency.

Molecular nanomagnets with competing interactions as optimal units for qudit-based quantum computation

Quantum systems displaying many accessible levels could be very powerful units of forthcoming quantum computing architectures. Indeed, the large number of available states could significantly simplify the actual implementation of several algorithms. Here we show that artificial molecular spins are particularly suitable to realize such a platform. In particular, multispin molecules with competing interactions provide a large number of low-energy multiplets in which decoherence is strongly suppressed compared to a single spin $S$ and does not increase with the system size. This feature, combined with the proper connectivity between the multiplets, enables the implementation of complex operations with remarkable fidelity, thus fully unleashing the potential of the molecular approach. We demonstrate the power of this approach by numerically simulating the implementation of one- and two-qudit gates on realistic molecular systems.

Large-scale coherent Ising machine based on optoelectronic parametric oscillator

Ising machines based on analog systems have the potential to accelerate the solution of ubiquitous combinatorial optimization problems. Although some artificial spins to support large-scale Ising machines have been reported, e.g., superconducting qubits in quantum annealers and short optical pulses in coherent Ising machines, the spin stability is fragile due to the ultra-low equivalent temperature or optical phase sensitivity. In this paper, we propose to use short microwave pulses generated from an optoelectronic parametric oscillator as the spins to implement a large-scale Ising machine with high stability. The proposed machine supports 25,600 spins and can operate continuously and stably for hours. Moreover, the proposed Ising machine is highly compatible with high-speed electronic devices for programmability, paving a low-cost, accurate, and easy-to-implement way toward solving real-world optimization problems.

Distinguishing Multispin Interactions from Lower-Order Effects

Multispin interactions can be engineered with artificial quantum spins. However, it is challenging to verify such interactions experimentally. Here, we describe two methods to characterize the $n$-local coupling of $n$ spins. First, we analyze the variation of the transition energy of the static system as a function of local spin fields. Standard measurement techniques are employed to distinguish $n$-local interactions between up to five spins from lower-order contributions in the presence of noise and spurious fields and couplings. Second, we show a detection technique that relies on time-dependent driving of the coupling term. Generalizations to larger system sizes are analyzed for both static and dynamic detection methods and we find that the dynamic method is asymptotically optimal when increasing the system size. The proposed methods enable robust exploration of multispin interactions across a broad range of both coupling strengths and qubit modalities.

An Ising Hamiltonian solver based on coupled stochastic phase-transition nano-oscillators

Combinatorial optimization problems belong to the non-deterministic polynomial time (NP)-hard complexity class, and their computational requirements scale exponentially with problem size. They can be mapped into the problem of finding the ground state of an Ising model, which describes a physical system with converging dynamics. Various platforms, including optical, electronic and quantum approaches, have been explored to accelerate the ground-state search, but improvements in energy efficiencies and computational abilities are still required. Here we report an Ising solver based on a network of electrically coupled phase-transition nano-oscillators (PTNOs) that form a continuous-time dynamical system (CTDS). The bi-stable phases of the injection-locked PTNOs act as artificial Ising spins and the stable points of the CTDS act as the ground-state solution of the problem. We experimentally show that a prototype with eight PTNOs can solve an NP-hard MaxCut problem with high probability of success (96% for 600 annealing cycles). We also show via numerical simulations that our Ising Hamiltonian solver can solve MaxCut problems of 100 nodes with energy efficiency of 1.3 × 107 solutions per second per watt, offering advantages over other approaches including memristor-based Hopfield networks, quantum annealers and photonic Ising solvers. An Ising solver that is based on a network of electrically coupled phase-transition nano-oscillators, which provides a continuous-time dynamical system, can be used to efficiently solve a non-deterministic polynomial time (NP)-hard MaxCut problem.

Application of THz ESR on Artificial Giant Spins in Magnetic Molecules

Varieties of magnetic molecules have been developed in decades to create novel functional magnetic materials and one of the goals is the creation of giant spin beyond the spins found in natural elements. THz ESR-experiments have been intensively used to study these spins because of the capability to determine of the spin sizes, anisotropies, symmetries, exchange couplings, and mixings among different states. These parameters are keys to control the functionality of the spins and their quantum mechanical behaviors. This review introduces examples of applications of THz ESR to determine these essential parameters.

From cavity to circuit quantum electrodynamics

Circuit quantum electrodynamics focuses on the interaction of small superconducting circuits, tailored to behave as two-level quantum systems, with a single mode of the electromagnetic field sustained by a superconducting resonator. It is thus concerned with the investigation of phenomena that arise from the coupling between the simplest non-trivial quantum system — a spin-1/2 or qubit — and a harmonic oscillator. As such, circuit quantum electrodynamics belongs to the more general field of cavity quantum electrodynamics, which deals with natural or artificial spins in the optical, microwave or radio-frequency domains interacting with all kind of resonators. Here we survey the lineage of the concepts and experiments that led first to the development of cavity and then circuit quantum electrodynamics. We discuss similarities and differences between these two fields and compare their present achievements. This article puts in perspective the relationship between cavity and circuit quantum electrodynamics, two related approaches for studying the fundamental quantum interaction between light and matter.

Breaking limitation of quantum annealer in solving optimization problems under constraints

Quantum annealing is a generic solver for optimization problems that uses fictitious quantum fluctuation. The most groundbreaking progress in the research field of quantum annealing is its hardware implementation, i.e., the so-called quantum annealer, using artificial spins. However, the connectivity between the artificial spins is sparse and limited on a special network known as the chimera graph. Several embedding techniques have been proposed, but the number of logical spins, which represents the optimization problems to be solved, is drastically reduced. In particular, an optimization problem including fully or even partly connected spins suffers from low embeddable size on the chimera graph. In the present study, we propose an alternative approach to solve a large-scale optimization problem on the chimera graph via a well-known method in statistical mechanics called the Hubbard-Stratonovich transformation or its variants. The proposed method can be used to deal with a fully connected Ising model without embedding on the chimera graph and leads to nontrivial results of the optimization problem. We tested the proposed method with a number of partition problems involving solving linear equations and the traffic flow optimization problem in Sendai and Kyoto cities in Japan.

A poor man\u2019s coherent Ising machine based on opto-electronic feedback systems for solving optimization problems

Coherent Ising machines (CIMs) constitute a promising approach to solve computationally hard optimization problems by mapping them to ground state searches of the Ising model and implementing them with optical artificial spin-networks. However, while CIMs promise speed-ups over conventional digital computers, they are still challenging to build and operate. Here, we propose and test a concept for a fully programmable CIM, which is based on opto-electronic oscillators subjected to self-feedback. Contrary to current CIM designs, the artificial spins are generated in a feedback induced bifurcation and encoded in the intensity of coherent states. This removes the necessity for nonlinear optical processes or large external cavities and offers significant advantages regarding stability, size and cost. We demonstrate a compact setup for solving MAXCUT optimization problems on regular and frustrated graphs with 100 spins and can report similar or better performance compared to CIMs based on degenerate optical parametric oscillators.

MRI-Inspired High-Resolution Localization for Biomedical Applications: Artificial Nuclear Spins on a Chip

Significant advances have been made recently toward technologies such as smart pills to image the gastrointestinal tract [1], distributed sensors to map the function of the brain [2], and microscale swimming robots to access organs through the bloodstream [3]. Such technologies promise new ways to diagnose and treat diseases of local pathology, including neurodegeneration, autoimmune disease, cancer, and atherosclerosis. In fact, wireless microscale devices that navigate the body to diagnose and treat disease are key elements of the future of medicine, addressing localized malfunction in neurological, cardiovascular, autoimmune, cancer, and other disease areas.

10 GHz clock time-multiplexed degenerate optical parametric oscillators for a photonic Ising spin network.

A coherent Ising machine based on degenerate optical parametric oscillators (DOPOs) is drawing attention as a way to find a solution to the ground-state search problem of the Ising model. Here we report the generation of time-multiplexed DOPOs at a 10 GHz clock frequency. We successfully generated >50,000 DOPOs using dual-pump four-wave mixing in a highly nonlinear fiber that formed a 1 km cavity, and observed phase bifurcation of the DOPOs, which suggests that the DOPOs can be used as stable artificial spins. In addition, we demonstrated the generation of more than 1 million DOPOs by extending the cavity length to 21 km. We also confirmed that the binary numbers obtained from the DOPO phase-difference measurement passed the NIST random number test, which suggests that we can obtain unbiased artificial spins.

Large-scale Ising spin network based on degenerate optical parametric oscillators

Simulating a network of Ising spins with physical systems is now emerging as a promising approach for solving mathematically intractable problems. Here we report a large-scale network of artificial spins based on degenerate optical parametric oscillators (DOPO), paving the way towards a photonic Ising machine capable of solving difficult combinatorial optimization problems. We generated >10,000 time-division-multiplexed DOPOs using dual-pump four-wave mixing (FWM) in a highly nonlinear fibre (HNLF) placed in a fibre cavity. Using those DOPOs, a one-dimensional (1D) Ising model was simulated by introducing nearest-neighbour optical coupling. We observed the formation of spin domains and found that the domain size diverged near the DOPO threshold, which suggests that the DOPO network can simulate the behavior of low-temperature Ising spins.

A new look on the two-dimensional Ising model: thermal artificial spins

We present a direct experimental investigation of the thermal ordering in an artificial analogue of an asymmetric two-dimensional Ising system composed of a rectangular array of nano-fabricated magnetostatically interacting islands. During fabrication and below a critical thickness of the magnetic material the islands are thermally fluctuating and thus the system is able to explore its phase space. Above the critical thickness the islands freeze-in resulting in an arrested thermalized state for the array. Determining the magnetic state we demonstrate a genuine artificial two-dimensional Ising system which can be analyzed in the context of nearest neighbor interactions.

Using the J1–J2 quantum spin chain as an adiabatic quantum data bus

This paper investigates numerically a phenomenon which can be used to transport a single q-bit down a J1–J2 Heisenberg spin chain using a quantum adiabatic process. The motivation for investigating such processes comes from the idea that this method of transport could potentially be used as a means of sending data to various parts of a quantum computer made of artificial spins, and that this method could take advantage of the easily prepared ground state at the so-called Majumdar–Ghosh point. We examine several annealing protocols for this process and find similar results for all of them. The annealing process works well up to a critical frustration threshold. There is also a brief section examining what other models this protocol could be used for, examining its use in the XXZ and XYZ models.

Melting artificial spin ice

Artificial spin ice arrays of micromagnetic islands are a means of engineering additional energy scales and frustration into magnetic materials. Here we demonstrate a magnetic phase transition in an artificial square spin ice and use the symmetry of the lattice to verify the presence of excitations far below the ordering temperature. We do this by measuring the temperature-dependent magnetization in different principal directions and comparing it with simulations of idealized statistical mechanical models. Our results confirm a dynamical pre-melting of the artificial spin ice structure at a temperature well below the intrinsic ordering temperature of the island material. We thus create a spin ice array that has the real thermal dynamics of artificial spins over an extended temperature range.