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| Hauptverfasser: | , , , , , , , , , , |
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| Format: | Preprint |
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2024
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| Online-Zugang: | https://arxiv.org/abs/2412.10317 |
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| author | Adeyeye, Temitayo N. Gibeault, Sidra Lathrop, Daniel P. Daniels, Matthew W. Stiles, Mark D. McClelland, Jabez J. Borders, William A. Ryan, Jason T. Talatchian, Philippe Ebels, Ursula Madhavan, Advait |
| author_facet | Adeyeye, Temitayo N. Gibeault, Sidra Lathrop, Daniel P. Daniels, Matthew W. Stiles, Mark D. McClelland, Jabez J. Borders, William A. Ryan, Jason T. Talatchian, Philippe Ebels, Ursula Madhavan, Advait |
| contents | In the superparamagnetic regime, magnetic tunnel junctions switch between two resistance states due to random thermal fluctuations. The dwell time distribution in each state is exponential. We sample this distribution using a temporal encoding scheme, in which information is encoded in the time at which the device switches between its resistance states. We then develop a circuit element known as a probabilistic delay cell that applies an electrical current step to a superparamagnetic tunnel junction and a temporal measurement circuit that measures the timing of the first switching event. Repeated experiments confirm that these times are exponentially distributed. Temporal processing methods then allow us to digitally compute with these exponentially distributed probabilistic delay cells. We describe how to use these circuits in a Metropolis-Hastings stepper and in a weighted random sampler, both of which are computationally intensive applications that benefit from the efficient generation of exponentially distributed random numbers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_10317 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Sampling from exponential distributions in the time domain with superparamagnetic tunnel junctions Adeyeye, Temitayo N. Gibeault, Sidra Lathrop, Daniel P. Daniels, Matthew W. Stiles, Mark D. McClelland, Jabez J. Borders, William A. Ryan, Jason T. Talatchian, Philippe Ebels, Ursula Madhavan, Advait Emerging Technologies In the superparamagnetic regime, magnetic tunnel junctions switch between two resistance states due to random thermal fluctuations. The dwell time distribution in each state is exponential. We sample this distribution using a temporal encoding scheme, in which information is encoded in the time at which the device switches between its resistance states. We then develop a circuit element known as a probabilistic delay cell that applies an electrical current step to a superparamagnetic tunnel junction and a temporal measurement circuit that measures the timing of the first switching event. Repeated experiments confirm that these times are exponentially distributed. Temporal processing methods then allow us to digitally compute with these exponentially distributed probabilistic delay cells. We describe how to use these circuits in a Metropolis-Hastings stepper and in a weighted random sampler, both of which are computationally intensive applications that benefit from the efficient generation of exponentially distributed random numbers. |
| title | Sampling from exponential distributions in the time domain with superparamagnetic tunnel junctions |
| topic | Emerging Technologies |
| url | https://arxiv.org/abs/2412.10317 |