다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Numerical Initial Value Problems in Ordinary Differential Equations

International Technology Roadmap for Semiconductors 2003の要求清浄度について － シリコンウエハ表面と雰囲気環境に要求される清浄度, 分析方法の現状について －

Unconventional, special-purpose machines may aid in accelerating the solution of some of the hardest problems in computing, such as large-scale combinatorial optimizations, by exploiting different operating mechanisms than those of standard digital computers. We present a scalable optical processor with electronic feedback that can be realized at large scale with room-temperature technology. Our prototype machine is able to find exact solutions of, or sample good approximate solutions to, a variety of hard instances of Ising problems with up to 100 spins and 10,000 spin-spin connections.

/pdf/a-fully-programmable-100-spin-coherent-ising-machine-with-inaxlu4ff3.pdf

A fully programmable 100-spin coherent Ising machine with all-to-all connections

In spin Hall nano-oscillators (SHNOs), pure spin currents drive local regions of magnetic films and nanostructures into auto-oscillating precession. If such regions are placed in close proximity to each other they can interact and may mutually synchronize. Here, we demonstrate robust mutual synchronization of two-dimensional SHNO arrays ranging from 2 × 2 to 8 × 8 nano-constrictions, observed both electrically and using micro-Brillouin light scattering microscopy. On short time scales, where the auto-oscillation linewidth $$\Delta f$$ is governed by white noise, the signal quality factor, $$Q=f/\Delta f$$, increases linearly with the number of mutually synchronized nano-constrictions (N), reaching 170,000 in the largest arrays. We also show that SHNO arrays exposed to two independently tuned microwave frequencies exhibit the same synchronization maps as can be used for neuromorphic vowel recognition. Our demonstrations may hence enable the use of SHNO arrays in two-dimensional oscillator networks for high-quality microwave signal generation and ultra-fast neuromorphic computing. Synchronization of oscillators can be used to carry out cognitive tasks. Large two-dimensional arrays of synchronized spin Hall nano-oscillators have now been demonstrated, and may in future enable neuromorphic computing on the nanoscale.

/pdf/two-dimensional-mutually-synchronized-spin-hall-nano-22zy3vcis4.pdf

Two-dimensional mutually synchronized spin Hall nano-oscillator arrays for neuromorphic computing

We present a new way to make Ising machines, i.e., using networks of coupled self-sustaining nonlinear oscillators. Our scheme is theoretically rooted in a novel result that establishes that the phase dynamics of coupled oscillator systems, under the influence of subharmonic injection locking, are governed by a Lyapunov function that is closely related to the Ising Hamiltonian of the coupling graph. As a result, the dynamics of such oscillator networks evolve naturally to local minima of the Lyapunov function. Two simple additional steps (i.e., adding noise, and turning subharmonic locking on and off smoothly) enable the network to find excellent solutions of Ising problems. We demonstrate our method on Ising versions of the MAX-CUT and graph colouring problems, showing that it improves on previously published results on several problems in the G benchmark set. Our scheme, which is amenable to realisation using many kinds of oscillators from different physical domains, is particularly well suited for CMOS IC implementation, offering significant practical advantages over previous techniques for making Ising machines. We present working hardware prototypes using CMOS electronic oscillators.

OIM: Oscillator-Based Ising Machines for Solving Combinatorial Optimisation Problems

Many combinatorial optimization problems can be mapped to finding the ground states of the corresponding Ising Hamiltonians. The physical systems that can solve optimization problems in this way, namely Ising machines, have been attracting more and more attention recently. Our work shows that Ising machines can be realized using almost any nonlinear self-sustaining oscillators with logic values encoded in their phases. Many types of such oscillators are readily available for large-scale integration, with potentials in high-speed and low-power operation. In this paper, we describe the operation and mechanism of oscillator-based Ising machines. The feasibility of our scheme is demonstrated through several examples in simulation and hardware, among which a simulation study reports average solutions exceeding those from state-of-art Ising machines on a benchmark combinatorial optimization problem of size 2000.

Oscillator-based Ising Machine.

In this paper, we report new results on a novel Ising machine technology for solving combinatorial optimization problems using networks of coupled self-sustaining oscillators. Specifically, we present several working hardware prototypes using CMOS electronic oscillators, built on bread-boards/perfboards and PCBs, implementing Ising machines consisting of up to 240 spins with programmable couplings. We also report that, just by simulating the differential equations of such Ising machines of larger sizes, good solutions can be achieved easily on benchmark optimization problems, demonstrating the effectiveness of oscillator-based Ising machines.

https://dl.acm.org/doi/pdf/10.1145/3316781.3322473

New Computational Results and Hardware Prototypes for Oscillator-based Ising Machines

Existing compact models for memristive devices (including RRAM and CBRAM) all suffer from issues related to mathematical ill-posedness and/or improper implementation. This limits their value for simulation and design and in some cases, results in qualitatively unphysical predictions. We identify the causes of ill-posedness in these models. We then show how memristive devices in general can be modelled using only continuous/smooth primitives in such a way that they always respect physical bounds for filament length and also feature well-defined and correct DC behaviour. We show how to express these models properly in languages like Verilog-A and ModSpec (MATLAB). We apply these methods to correct previously published RRAM and memristor models and make them well posed. The result is a collection of memristor models that may be dubbed "simulation-ready", i.e., that feature the right physical characteristics and are suitable for robust and consistent simulation in DC, AC, transient, etc., analyses. We provide implementations of these models in both ModSpec/MATLAB and Verilog-A.

Well-Posed Models of Memristive Devices.

In this paper we take a fresh look at Goto and von Neumann’s phase-based logic ideas, provide enhancements that can overcome major limitations of their previous implementations. We show that with injection locking serving as the central mechanism, almost any DC-powered, self-sustaining nonlinear oscillator — including electronic, spintronic, biological, optical and mechanical ones — can be used to build fundamental components — including latches and combinatorial elements in a phase logic based computing architecture. We also discuss noise immunity and potential power dissipation advantages that can be achieved under this scheme.

Tianshi Wang

Papers

OIM: Oscillator-Based Ising Machines for Solving Combinatorial Optimisation Problems

Oscillator-based Ising Machine.

New Computational Results and Hardware Prototypes for Oscillator-based Ising Machines

Well-Posed Models of Memristive Devices.

PHLOGON: PHase-based LOGic using Oscillatory Nano-systems