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Quantum Annealing (QA)-accelerated MIMO detection is an emerging research approach in the context of NextG wireless networks. The opportunity is to enable large MIMO systems and thus improve wireless performance. The approach aims to leverage QA to expedite the computation required for theoretically optimal but computationally-demanding Maximum Likelihood detection to overcome the limitations of the currently deployed linear detectors. This paper presents X-ResQ, a QA-based MIMO detector system featuring flexible parallelism that is uniquely enabled by quantum Reverse Annealing (RA). Unlike prior designs, X-ResQ has many desirable parallel QA system properties and has effectively improved detection performance as more qubits are assigned. In our evaluations on a state-of-the-art quantum annealer, fully parallel X-ResQ achieves near-optimal throughput for 4 ×6 MIMO with 16-QAM using approx. 240 qubits achieving 2.5–5× gains compared against other classical and quantum detectors. We also implement and evaluate X-ResQ in the non-quantum digital setting for more comprehensive evaluations. This classical X-ResQ showcases the potential to realize ultra-large 1024 ×1024 MIMO, significantly outperforming other MIMO detectors, including the state-of-the-art RA detector classically implemented in the same way. 

Upon osmotic compression, rotationally symmetric faceted colloidal particles can form translationally ordered, orientationally disordered rotator mesophases. This study explores the mechanism of rotator-to-crystal phase transitions where orientational order is gained in a translationally ordered phase, using rotator-phase forming truncated cubes as a testbed. Monte Carlo simulations were conducted for two selected truncations (s), one for s = 0.527 where the rotator and crystal lattices are dissimilar and one for s = 0.572 where the two phases have identical lattices. These differences set the stage for a qualitative difference in their rotator–crystal transitions, highlighting the effect of lattice distortion on phase transition kinetics. Our simulations reveal that significant lattice deviatoric effects could hinder the rotator-to-crystal transition and favor arrangements of lower packing fraction instead. Indeed, upon compression, it is found that for s = 0.527, the rotator phase does not spontaneously transition into the stable, densely packed crystal due to the high lattice strains involved but instead transitions into a metastable solid phase to be colloquially referred to as “orientational salt” for short, which has a similar lattice as the rotator phase and exhibits two distinct particle orientations having substitutional order, alternating regularly throughout the system. This study paves the way for further analysis of diffusionless transformations in nanoparticle systems and how lattice-distortion could influence crystallization kinetics. 

Unlike the well-studied and technologically advanced Group III-V and Group II-VI compound semiconductor alloys, alloys of ternary metal oxide semiconductors have only recently begun to receive widespread attention. Here, we describe the effect of alkaline earth metal substitution on the optical, electronic, and photoelectrochemical (PEC) properties of copper metavanadate (CuV₂O₆). As a host, the Cu-V-O compound family presents a versatile framework to develop such composition-property correlations. Alloy compositions of A_0.1Cu_0.9V₂O₆(A = Mg, Ca) photoanodes were synthesized via a time and energy-efficient solution combustion synthesis (SCS) method. The effect of introducing alkaline earth metals (Mg, Ca) on the crystal structure, microstructure, electronic, and optical properties of copper metavanadates was investigated by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), diffuse reflectance spectroscopy (DRS), transmission electron microscopy (TEM), and Raman spectroscopy. The PXRD, TEM, and Raman spectroscopy data demonstrated the polycrystalline powder samples to be mutually soluble, solid solutions of copper and alkaline earth metal metavanadates and not simple mixtures of these compounds. The DRS data showed a systematic decrease in the optical bandgap with Cu incorporation. These trends were corroborated by electronic band structure calculations. Finally, the PEC properties exhibited a strong dependence on the alloy composition, pointing to possible applicability in solar water splitting, heterogeneous photocatalysis, phosphor lighting/displays, and photovoltaic devices. 

Neuromorphic computation is based on spike trains in which the location and frequency of spikes occurring within the network guide the execution. This paper develops a frame-work to monitor the correctness of a neuromorphic program’s execution using model-based redundancy in which a software-based monitor compares discrepancies between the behavior of neurons mapped to hardware and that predicted by a corresponding mathematical model in real time. Our approach reduces the hardware overhead needed to support the monitoring infrastructure and minimizes intrusion on the executing application. Fault-injection experiments utilizing CARLSim, a high-fidelity SNN simulator, show that the framework achieves high fault coverage using parsimonious models which can operate with low computational overhead in real time.