A 50-spin surface acoustic wave Ising machine

Time-multiplexed Spinwave Ising Machines (SWIMs) have unveiled a route towards miniaturized, low-cost, and low-power solvers of combinatorial optimization problems. While the number of supported spins is limited by the nonlinearity of the spinwave dispersion, other collective excitations, such as surface acoustic waves (SAWs), offer a linear dispersion. Here, we demonstrate an all-to-all, fully FPGA reprogrammable, 50-spin surface acoustic wave-based Ising machine (SAWIM), using a 50-mm-long Lithium Niobate SAW delay line, off-the-shelf microwave components, and a low-cost FPGA. The SAWIM can solve any 50-spin MAX-CUT problem, with arbitrary coupling matrices, in less than 340 $\mu$s consuming only 0.62 mJ, corresponding to close to 3000 solutions per second and a figure of merit of 1610 solutions/W/s. We compare the SAWIM computational results with those of a 100-spin optical Coherent Ising machine and find a higher probability of solution. Moreover, we demonstrate that there is an optimum overall coupling strength between spins at which the probability of the exact solution reaches 100%. The SAWIM illustrates the general merits of solid state wave-based time-multiplexed Ising machines in the microwave domain as versatile platforms for commercially feasible high-performance solvers of combinatorial optimization problems

Towards Hybrid Classical-Quantum Computation Structures in Wirelessly-Networked Systems

With unprecedented increases in traffic load in today's wireless networks, design challenges shift from the wireless network itself to the computational support behind the wireless network. In this vein, there is new interest in quantum-compute approaches because of their potential to substantially speed up processing, and so improve network throughput. However, quantum hardware that actually exists today is much more susceptible to computational errors than silicon-based hardware, due to the physical phenomena of decoherence and noise. This paper explores the boundary between the two types of computation---classical-quantum hybrid processing for optimization problems in wireless systems---envisioning how wireless can simultaneously leverage the benefit of both approaches. We explore the feasibility of a hybrid system with a real hardware prototype using one of the most advanced experimentally available techniques today, reverse quantum annealing. Preliminary results on a low-latency, large MIMO system envisioned in the 5G New Radio roadmap are encouraging, showing approximately 2--10X better performance in terms of processing time than prior published results.Comment: HotNets 2020: Nineteenth ACM Workshop on Hot Topics in Networks (https://doi.org/10.1145/3422604.3425924

A Channel Selection Model based on Trust Metrics for Wireless Communications

Dynamic allocation of frequency resources to nodes in a wireless communication network is a well-known method adopted to mitigate potential interference, both unintentional and malicious. Various selection approaches have been adopted in literature, to limit the impact of interference and keep a high quality of wireless links. In this paper, we propose a different channel selection method, based on trust policies. The trust management approach proposed in this work relies on the node’s own experience and trust recommendations provided by its neighbourhood. By means of simulation results in Network Simulator NS-3, we demonstrate the effectiveness of the proposed trust method, while the system is under jamming attacks, in respect of a baseline approach. We also consider and evaluate the resilience of our approach in respect of malicious nodes, providing false information regarding the quality of the channel, to induct bad channel selection of the node. Results show how the system is resilient in respect of malicious nodes, keeping around 10% of throughput more than an approach only based on the own proper experience, considering the presence of 40% of malicious nodes, both single and collusive attacks

A Cost and Power Feasibility Analysis of Quantum Annealing for NextG Cellular Wireless Networks

In order to meet mobile cellular users' ever-increasing data demands, today's 4 G and 5 G wireless networks are designed mainly with the goal of maximizing spectral efficiency. While they have made progress in this regard, controlling the carbon footprint and operational costs of such networks remains a long-standing problem among network designers. This paper takes a long view on this problem, envisioning a NextG scenario where the network leverages quantum annealing for cellular baseband processing. We gather and synthesize insights on power consumption, computational throughput and latency, spectral efficiency, operational cost, and feasibility timelines surrounding quantum annealing technology. Armed with these data, we project the quantitative performance targets future quantum annealing hardware must meet in order to provide a computational and power advantage over CMOS hardware, while matching its whole-network spectral efficiency. Our quantitative analysis predicts that with 82.32 μ s problem latency and 2.68 M qubits, quantum annealing will achieve a spectral efficiency equal to CMOS while reducing power consumption by 41 kW (45% lower) in a Large MIMO base station with 400 MHz bandwidth and 64 antennas, and a 160 kW power reduction (55% lower) using 8.04 M qubits in a CRAN setting with three Large MIMO base stations

Leveraging Quantum Annealing for Large MIMO Processing in Centralized Radio Access Networks

User demand for increasing amounts of wireless capacity continues to outpace supply, and so to meet this demand, significant progress has been made in new MIMO wireless physical layer techniques. Higher-performance systems now remain impractical largely only because their algorithms are extremely computationally demanding. For optimal performance, an amount of computation that increases at an exponential rate both with the number of users and with the data rate of each user is often required. The base station's computational capacity is thus becoming one of the key limiting factors on wireless capacity. QuAMax is the first large MIMO centralized radio access network design to address this issue by leveraging quantum annealing on the problem. We have implemented QuAMax on the 2,031 qubit D-Wave 2000Q quantum annealer, the state-of-the-art in the field. Our experimental results evaluate that implementation on real and synthetic MIMO channel traces, showing that 10~$\mu$s of compute time on the 2000Q can enable 48 user, 48 AP antenna BPSK communication at 20 dB SNR with a bit error rate of $10^{-6}$ and a 1,500 byte frame error rate of $10^{-4}$.Comment: https://dl.acm.org/doi/10.1145/3341302.334207

Entangled-photon decision maker

The competitive multi-armed bandit (CMAB) problem is related to social issues such as maximizing total social benefits while preserving equality among individuals by overcoming conflicts between individual decisions, which could seriously decrease social benefits. The study described herein provides experimental evidence that entangled photons physically resolve the CMAB in the 2-arms 2-players case, maximizing the social rewards while ensuring equality. Moreover, we demonstrated that deception, or outperforming the other player by receiving a greater reward, cannot be accomplished in a polarization-entangled-photon-based system, while deception is achievable in systems based on classical polarization-correlated photons with fixed polarizations. Besides, random polarization-correlated photons have been studied numerically and shown to ensure equality between players and deception prevention as well, although the CMAB maximum performance is reduced as compared with entangled photon experiments. Autonomous alignment schemes for polarization bases were also experimentally demonstrated based only on decision conflict information observed by an individual without communications between players. This study paves a way for collective decision making in uncertain dynamically changing environments based on entangled quantum states, a crucial step toward utilizing quantum systems for intelligent functionalities

Smart Surface Radio Environments

This Roadmap takes the reader on a journey through the research in electromagnetic wave propagation control via reconfigurable intelligent surfaces. Metasurface modelling and design methods are reviewed along with physical realisation techniques. Several wireless applications are discussed, including beam-forming, focusing, imaging, localisation, and sensing, some rooted in novel architectures for future mobile communications networks towards 6G

組合せ最適化問題のための測定フィードバック型コヒーレント・イジングマシンの実現と評価

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 合原 一幸, 東京大学教授 岩田 覚, 東京大学准教授 平田 祥人, 東京大学准教授 大西 立顕, 東京大学准教授 鈴木 大慈University of Tokyo(東京大学

2022 roadmap on neuromorphic computing and engineering

Modern computation based on von Neumann architecture is now a mature cutting-edge science. In the von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer is responsible for a large part of the power consumption. The next generation computer technology is expected to solve problems at the exascale with 10$^{18}$ calculations each second. Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically built-in capabilities to learn or deal with complex data as our brain does. These needs can be addressed by neuromorphic computing systems which are inspired by the biological concepts of the human brain. This new generation of computers has the potential to be used for the storage and processing of large amounts of digital information with much lower power consumption than conventional processors. Among their potential future applications, an important niche is moving the control from data centers to edge devices. The aim of this roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the challenges and opportunities that the future holds in the major areas of neuromorphic technology, namely materials, devices, neuromorphic circuits, neuromorphic algorithms, applications, and ethics. The roadmap is a collection of perspectives where leading researchers in the neuromorphic community provide their own view about the current state and the future challenges for each research area. We hope that this roadmap will be a useful resource by providing a concise yet comprehensive introduction to readers outside this field, for those who are just entering the field, as well as providing future perspectives for those who are well established in the neuromorphic computing community