A group of researchers from Bar-Ilan University have found a way to stabilize and control an "exponential number of discrete magnetic states," which they hope will create an avenue to multi-level magnetic memory, the university announced on Monday.These types of advancements could be used towards storing data, magnetic sensing as well as neuromorphic computing - which incorporates using a large-scale system of integrated circuits to mirror the neuro-biological design of the nervous system - among other uses. "This finding may pave the way to multi-level magnetic memory with extremely large number of states per cell (e.g., 256 states when N=4), be used for neuromorphic computing, and more," said lead researcher Prof. Lior Klein of Bar-Ilan's physics department and the Institute of Nanotechnology and Advanced Materials.The study itself, which appeared as the feature article in the June issue of Applied Physics Letters, focused on magnetic thin films aligned in the form of an N crossing ellipses, possessing two to the power of 2N magnetization states. During the study they demonstrated that they could switch between magnetic states by simply generating differing spin currents, and through trial and error they found the ability to stabilize and control an exponential number of discrete magnetic states "in a relatively simple structure" - which they add is major step forward in the field of spintronics. While it was hypothesized that these simple structures could definitely house an exponential number of magnetic states, the actual amount was "much greater" than expected."Spintronics devices commonly consist of magnetic elements manipulated by spin-polarized currents between stable magnetic states. When spintronic devices are used for storing data, the number of stable states sets an upper limit on memory capacity." Bar-Ilan explained in a statement. "While current commercial magnetic memory cells have two stable magnetic states corresponding to two memory states, there are clear advantages to increasing this number, as it will potentially allow increasing the memory density and enable the design of novel types of memory."