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Generation of Tunable Stochastic Sequences Using the Insulator–Metal Transition

Javier del Valle, Pavel Salev, Stefano Gariglio, Yoav Kalcheim, Iván K. Schuller, Jean‐Marc Triscone

2022Nano Letters34 citationsDOIOpen Access PDF

Abstract

Probabilistic computing is a paradigm in which data are not represented by stable bits, but rather by the probability of a metastable bit to be in a particular state. The development of this technology has been hindered by the availability of hardware capable of generating stochastic and tunable sequences of “1s” and “0s”. The options are currently limited to complex CMOS circuitry and, recently, magnetic tunnel junctions. Here, we demonstrate that metal–insulator transitions can also be used for this purpose. We use an electrical pump/probe protocol and take advantage of the stochastic relaxation dynamics in VO2 to induce random metallization events. A simple latch circuit converts the metallization sequence into a random stream of 1s and 0s. The resetting pulse in between probes decorrelates successive events, providing a true stochastic digital sequence.

Topics & Concepts

Probabilistic logicMetastabilityCMOSSequence (biology)Stochastic processInsulator (electricity)Random accessStochastic computingBistabilityMetal–insulator transitionComputer scienceElectronic circuitMaterials scienceOptoelectronicsPhysicsElectrical engineeringMathematicsMetalChemistryEngineeringQuantum mechanicsMetallurgyStatisticsBiochemistryArtificial intelligenceOperating systemAdvanced Memory and Neural ComputingNeural Networks and Reservoir ComputingError Correcting Code Techniques
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