Related papers: CMOS-integrated superparamagnetic tunnel junction-…
For decades, semiconductors and their heterostructures have underpinned both fundamental and applied research across all areas of electronics. Two-dimensional, 2D (atomically thin) semiconductors have now the potential to push further the…
Control of magnetism without using magnetic fields enables large-scale integration of spintronic devices for memory, computation and communication in the beyond-CMOS era. Mechanisms including spin torque transfer, spin Hall effect, and…
The search of hardware-compatible strategies for solving NP-hard combinatorial optimization problems (COPs) is an important challenge of today s computing research because of their wide range of applications in real world optimization…
Electric-field control of spin states offers a promising route to ultra-low-power, ultra-fast magnetization switching in spintronic devices such as magnetic tunnel junctions (MTJs). Recent progress in modulating spin-orbit interactions at…
The possible use of spin and magnets in place of charge and capacitors to store and process information is well known. Magnetic tunnel junctions are being widely investigated and developed for magnetic random access memories. These are two…
Antiferromagnetic Tunnel Junctions (AFMTJs) enable picosecond switching and femtojoule writes through ultrafast sublattice dynamics. We present the first end-to-end AFMTJ simulation framework integrating multi-sublattice…
The large-scale fabrication of three-terminal magnetic tunnel junctions (MTJs) with high yield is becoming increasingly crucial, especially with the growing interest in spin-orbit torque (SOT) magnetic random access memory (MRAM) as the…
The probability switching characteristics in spin transfer torque magnetic tunnel junctions (STT-MTJs) are simulated by considering thermal noise using a spin-circuit module. Thermal noise significantly affects the probability switching for…
The reproducibility of qubit parameters is a challenge for scaling up superconducting quantum processors. Signal crosstalk imposes constraints on the frequency separation between neighboring qubits. The frequency uncertainty of transmon…
Conventional computing paradigm struggles to fulfill the rapidly growing demands from emerging applications, especially those for machine intelligence, because much of the power and energy is consumed by constant data transfers between…
Probabilistic computing is an emerging quantum-inspired computing paradigm capable of solving combinatorial optimization and various other classes of computationally hard problems. In this work, we present pc-COP, an efficient and…
We propose a new scalable platform for quantum computing (QC) -- an array of optically trapped symmetric-top molecules (STMs) of the alkaline earth monomethoxide (MOCH$_3$) family. Individual STMs form qubits, and the system is readily…
Molecular docking is a critical computational strategy in drug design and discovery, but the complex diversity of biomolecular structures and flexible binding conformations create an enormous search space that challenges conventional…
One of the biggest challenges the current STT-RAM industry faces is maintaining a high thermal stability while trying to switch within a given voltage pulse and energy cost. In this paper, we present a physics based analytical model that…
Spin filtering and its back-action spin transfer torque (STT) are key ingredients of latest spintronic devices based on magnetic tunnel junctions (MTJs). Resonant tunneling (RT), implemented by design or occurring as parasitic effects, is…
Probabilistic bit (p-bit)-based compute engines utilize the unique capability of a p-bit to probabilistically switch between two states to solve computationally challenging problems. However, when solving problems that require more than two…
Extremely long coherence times, excellent single-qubit gate fidelities and two-qubit logic have been demonstrated with silicon metal-oxide-semiconductor spin qubits, making it one of the leading platforms for quantum information processing.…
Josephson junctions constructed from superconductor-semiconductor-superconductor heterostructures have been used to realize a variety of voltage-tunable superconducting quantum devices, including qubits and parametric amplifiers. To date…
Stochastic spiking neural networks based on nanoelectronic spin devices can be a possible pathway to achieving "brainlike" compact and energy-effcient cognitive intelligence. The computational model attempt to exploit the intrinsic device…
Spins based in silicon provide one of the most promising architectures for quantum computing. Quantum dots are an inherently scalable technology. Here, we combine these two concepts into a workable design for a silicon-germanium quantum…