Independent Control of Antiparallel- and Parallel-State Thermal Stability Factors in Magnetic Tunnel Junctions for Telegraphic Signals With Two Degrees of Tunability

Zink, Brandon R.; Lv, Yang; Wang, Jianping

doi:10.1109/ted.2019.2948218

Cited by 12 publications

(4 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Matsumoto et al pointed out that n I rapidly decreases from 2 to 1.4 with increasing K 2 /K 1 eff from 0 to ~0.25 51 . Experimentally, some assumed 1 25,[27][28][29][30]36,39 whereas others assumed 2 26,[31][32][33] , and importantly no studies access the number. The present experimental results support the scenario of Matsumoto et al, but, similarly to n H , the reduction of n I is more moderate than the theoretical prediction.…”

Section: Discussionmentioning

confidence: 99%

“…Here we experimentally study the Néel-Arrhenius law of a nanomagnet under STT utilising superparamagnetic tunnel junctions that allow direct determination of the event time under fields and currents [34][35][36][37][38][39] . Through measurements of homodynedetected ferromagnetic resonance (FMR) under current biases, high-speed STT switching with various pulse widths, and random telegraph noise (RTN) under various fields and currents, values of n H and n I are uniquely determined for given conditions.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Local bifurcation with spin-transfer torque in superparamagnetic tunnel junctions

et al. 2022

View full text Add to dashboard Cite

Modulation of the energy landscape by external perturbations governs various thermally-activated phenomena, described by the Arrhenius law. Thermal fluctuation of nanoscale magnetic tunnel junctions with spin-transfer torque (STT) shows promise for unconventional computing, whereas its rigorous representation, based on the Néel-Arrhenius law, has been controversial. In particular, the exponents for thermally-activated switching rate therein, have been inaccessible with conventional thermally-stable nanomagnets with decade-long retention time. Here we approach the Néel-Arrhenius law with STT utilising superparamagnetic tunnel junctions that have high sensitivity to external perturbations and determine the exponents through several independent measurements including homodyne-detected ferromagnetic resonance, nanosecond STT switching, and random telegraph noise. Furthermore, we show that the results are comprehensively described by a concept of local bifurcation observed in various physical systems. The findings demonstrate the capability of superparamagnetic tunnel junction as a useful tester for statistical physics as well as sophisticated engineering of probabilistic computing hardware with a rigorous mathematical foundation.

show abstract

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Local bifurcation with spin-transfer torque in superparamagnetic tunnel junctions

et al. 2022

View full text Add to dashboard Cite

show abstract

“…One is that it can be used to generate stochastic switching signals in thermally stable MTJs as well as sMTJs [79]. Second is that the average switching rate of the signals generated can be tuned by over four orders of magnitude and reach switching rates above 1 MHz [79], [80], [81]. The third, and most unique, feature of dual biasing is that the two biases can control the AP-and P-state dwell times separately, which we refer to as two degrees of tunability, and implies that the average output and average switching rate can be tuned independently.…”

Section: Dual-biased Mtjs For Asynchronous Methodsmentioning

confidence: 99%

Review of Magnetic Tunnel Junctions for Stochastic Computing

Zink

Wang

2022

IEEE J. Explor. Solid-State Comput. Devices Circuits

Self Cite

View full text Add to dashboard Cite

Modern computing schemes require large circuit areas and large energy consumption for neuromorphic computing applications, such as recognition, classification, and prediction. This is because these tasks require parallel processing on large datasets. Stochastic computing (SC) is a promising alternative to conventional binary computing schemes due to its low area cost, low processing power, and robustness to noise. However, the large area and energy costs for random number generation with CMOS-based circuits make SC impractical for most hardware implementations. For this reason, beyond-CMOS approaches to random number generation have been investigated in recent years. Spintronics is one of the most promising approaches due to the intrinsic stochasticity of the magnetic tunnel junction (MTJ). In this review article, we provide an overview of the literature published in recent years investigating the tunable, intrinsic stochasticity of MTJs and proposing practical methods for random number generation using spintronic hardware.INDEX TERMS Magnetic tunnel junctions (MTJs), random number generators (RNGs), spintronic devices, stochastic-bit generators (SBGs), stochastic computing (SC).

show abstract

“…This has been demonstrated experimentally in ref. 48,49 where a stable MTJ was used as a bipolar resistor whose distribution was tuned by an external field. Fig.…”

Section: B Performing the Bsn Functionmentioning

confidence: 99%

Quantitative Evaluation of Hardware Binary Stochastic Neurons

Hassan

Datta

2021

Phys. Rev. Applied

View full text Add to dashboard Cite

Recently there has been increasing activity to build dedicated Ising Machines to accelerate the solution of combinatorial optimization problems by expressing these problems as a ground-state search of the Ising model. A common theme of such Ising Machines is to tailor the physics of underlying hardware to the mathematics of the Ising model to improve some aspect of performance that is measured in speed to solution, energy consumption per solution or area footprint of the adopted hardware. One such approach to build an Ising spin, or a binary stochastic neuron (BSN), is a compact mixed-signal unit based on a low-barrier nanomagnet based design that uses a single magnetic tunnel junction (MTJ) and three transistors (3T-1MTJ) where the MTJ functions as a stochastic resistor (1SR). Such a compact unit can drastically reduce the area footprint of BSNs while promising massive scalability by leveraging the existing Magnetic RAM (MRAM) technology that has integrated 1T-1MTJ cells in ∼ Gbit densities. The 3T-1SR design however can be realized using different materials or devices that provide naturally fluctuating resistances. Extending previous work, we evaluate hardware BSNs from this general perspective by classifying necessary and sufficient conditions to design a fast and energy-efficient BSN that can be used in scaled Ising Machine implementations. We connect our device analysis to systems-level metrics by emphasizing hardware-independent figures-of-merit such as flips per second and dissipated energy per random bit that can be used to classify any Ising Machine.

show abstract

Independent Control of Antiparallel- and Parallel-State Thermal Stability Factors in Magnetic Tunnel Junctions for Telegraphic Signals With Two Degrees of Tunability

Cited by 12 publications

References 19 publications

Local bifurcation with spin-transfer torque in superparamagnetic tunnel junctions

Local bifurcation with spin-transfer torque in superparamagnetic tunnel junctions

Review of Magnetic Tunnel Junctions for Stochastic Computing

Quantitative Evaluation of Hardware Binary Stochastic Neurons

Contact Info

Product

Resources

About