Capturing Exponential Variance Using Polynomial Resources: Applying Tensor Networks to Nonequilibrium Stochastic Processes
Estimating the expected value of an observable appearing in a nonequilibrium stochastic process usually involves sampling. If the observable’s variance is high, many samples are required. In contrast, we show that performing the same task without sampling, using tensor network compression, efficien...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
American Physical Society
2015
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