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Computational reversibility is necessary for quantum computation and inspires the development of computing systems in which information carriers are conserved as they flow through a circuit. While conservative logic provides an exciting vision for reversible computing with no energy dissipation, the large dimensions of information carriers in previous realizations detract from the system efficiency, and nanoscale conservative logic remains elusive. We therefore propose a non-volatile reversible computing system in which the information carriers are magnetic skyrmions, topologically-stable magnetic whirls. These nanoscale quasiparticles interact with one another via the spin-Hall and skyrmion-Hall effects as they propagate through ferromagnetic nanowires structured to form cascaded conservative logic gates. These logic gates can be directly cascaded in large-scale systems that perform complex logic functions, with signal integrity provided by clocked synchronization structures. The feasibility of the proposed system is demonstrated through micromagnetic simulations of Boolean logic gates, a Fredkin gate, and a cascaded full adder. As skyrmions can be transported in a pipelined and non-volatile manner at room temperature without the motion of any physical particles, this skyrmion logic system has the potential to deliver scalable high-speed low-power reversible Boolean and quantum computing.
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Magnetic skyrmions are exciting candidates for energy-efficient computing due to their non-volatility, detectability,and mobility. A recent proposal within the paradigm of reversible computing enables large-scale circuits composed ofdirectly-cascaded skyrmion logic gates, but it is limited by the manufacturing difficulty and energy costs associated withthe use of notches for skyrmion synchronization. To overcome these challenges, we therefore propose a skyrmion logicsynchronized via modulation of voltage-controlled magnetic anisotropy (VCMA). In addition to demonstrating theprinciple of VCMA synchronization through micromagnetic simulations, we also quantify the impacts of current den-sity, skyrmion velocity, and anisotropy barrier height on skyrmion motion. Further micromagnetic results demonstratethe feasibility of cascaded logic circuits in which VCMA synchronizers enable clocking and pipelining, illustrating afeasible pathway toward energy-efficient large-scale computing systems based on magnetic skyrmions.
Considering the large-scale quantum computer, it is important to know how much quantum computational resources is necessary precisely and quickly. Unfortunately the previous methods so far cannot support a large-scale quantum computing practically and therefore the analysis because they usually use a non-structured code. To overcome this problem, we propose a fast mapping by using the hierarchical assembly code which is much more compact than the non-structured code. During the mapping process, the necessary modules and their interconnection can be dynamically mapped by using the communication bus at the cost of additional qubits. In our study, the proposed method works very fast such as 1 hour than 1500 days for Shor algorithm to factorize 512-bit integer. Meanwhile, since the hierarchical assembly code has high degree of locality, it has shorter SWAP chains and hence it does not increase the quantum computation time than expected.
We examine skyrmions driven periodically over random quenched disorder and show that there is a transition from reversible motion to a state in which the skyrmion trajectories are chaotic or irreversible. We find that the characteristic time required for the system to organize into a steady reversible or irreversible state exhibits a power law divergence near a critical ac drive period, with the same exponent as that observed for reversible to irreversible transitions in periodically sheared colloidal systems, suggesting that the transition can be described as an absorbing phase transition in the directed percolation universality class. We compare our results to the behavior of an overdamped system and show that the Magnus term enhances the irreversible behavior by increasing the number of dynamically accessible orbits. We discuss the implications of this work for skyrmion applications involving the long time repeatable dynamics of dense skyrmion arrays.
Boolean algebra, the branch of mathematics where variables can assume only true or false value, is the theoretical basis of classical computation. The analogy between Boolean operations and electronic switching circuits, highlighted by Shannon in 1938, paved the way to modern computation based on electronic devices. The grow of computational power of such devices, after an exciting exponential -Moore trend, is nowadays blocked by heat dissipation due to computational tasks, very demanding after the chips miniaturization. Heat is often a detrimental form of energy which increases the systems entropy decreasing the efficiency of logic operations. Here, we propose a physical system able to perform thermal logic operations by reversing the old heat-disorder epitome into a novel heat-order paradigm. We lay the foundations of heat computation by encoding logic state variables in temperature and introducing the thermal counterparts of electronic logic gates. Exploiting quantum effects in thermally biased Josephson junctions (JJs), we propound a possible realization of a functionally complete dissipationless logic. Our architecture ensures high operation stability and robustness with switching frequencies reaching the GHz.
Neuromorphic computing with spintronic devices has been of interest due to the limitations of CMOS-driven von Neumann computing. Domain wall-magnetic tunnel junction (DW-MTJ) devices have been shown to be able to intrinsically capture biological neuron behavior. Edgy-relaxed behavior, where a frequently firing neuron experiences a lower action potential threshold, may provide additional artificial neuronal functionality when executing repeated tasks. In this study, we demonstrate that this behavior can be implemented in DW-MTJ artificial neurons via three alternative mechanisms: shape anisotropy, magnetic field, and current-driven soft reset. Using micromagnetics and analytical device modeling to classify the Optdigits handwritten digit dataset, we show that edgy-relaxed behavior improves both classification accuracy and classification rate for ordered datasets while sacrificing little to no accuracy for a randomized dataset. This work establishes methods by which artificial spintronic neurons can be flexibly adapted to datasets.
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