Using Novel Approaches for Navigating Complex Energy Landscapes: Ion Channel Conductance using Hyperdynamics and Human-Guided Global Optimization of Lennard-Jones Clusters

Molecular dynamics (MD) is a widely used tool to study molecular systems on atomic level. However, the timescale of a traditional MD simulation is typically limited to nanoseconds. Thus many interesting processes that occur on microseconds or larger timescale can\u27t be studied. Hyperdynamics provides a way to extend the timescale of MD simulation. In hyperdynamics, MD is performed on a biased potential then corrected to get true dynamics provided certain conditions are met. Here, we tried to study potassium channel conductance using the hyperdynamics method with a bias potential constructed based on the potential of mean force of ion translocation through the selective filter of a potassium ion channel. However, when MD was performed on this biased potential, no ion translocation events were observed. Although some new insights were gained into the rate-limiting steps for ion mobility in this system from these negative results, no further studies are planned with this project. The second project is based on the assumption that hybrid human{computational algorithm is more efficient than purely computational algorithm itself. Such ideas have already been studied by many \crowd-sourcing games, such as Foldit [1] for the protein structure prediction problem, and QuantumMoves [2] for quantum physics. Here, the same idea is applied to cluster structure optimization. A virtual reality android cellphone app was developed to study global optimization of Lennard-Jones clusters with both computational algorithm and hybrid human{computational algorithm. Using linear mixed model analysis, we found statistically significant differences between the expected runtime of both methods, at least for cluster of certain sizes. Further analysis of the data showing human intelligence weakened the strong dependence of the efficiency of the computational method on cluster sizes. We hypothesis that this is due to that humans are able to make large moves that allows the algorithm to cover a large region in the potential energy surface faster. Further studies with more cluster sizes are needed to draw a more complete conclusion. Human intelligence can potentially be integrated into more advanced optimization technique and applied to more complicated optimization problems in the future. Patterns analysis of human behaviors during the optimization process can be conducted to gain insights of mechanisms and strategies of optimization process

Mathematical Modeling of Deposition of Carbonaceous Material from Heavy Hydrocarbon Vapors

https://digitalrepository.unm.edu/abq_mj_news/4576/thumbnail.jp

Muon Anomalous Magnetic Moment and Higgs Potential Stability in the 331 Model from SU(6)SU(6)

We consider a $SU(3)_c \times SU(3)_L \times U(1)_X$ model from a $SU(6)$ Grand Unified Theory (GUT). In order to explain the anomalous magnetic moments of muon and electron, we introduce two new scalar triplets without vacuum expectation values (VEVs) so that the leading contributions to $\Delta a_{\mu}$ and $\Delta a_{e}$ can avoid the suppression from small muon mass. In addition, the Higgs potential stability of this 331 model is studied by giving a set of sufficient conditions to ensure the boundedness from below of the potential.Comment: 15 page

The ZZ resonance, inelastic dark matter, and new physics anomalies in the Simple Extension of the Standard Model (SESM) with general scalar potential

We consider the generic scalar potential with CP-violation, and study the $Z$ resonance and inelastic dark matter in the Simple Extension of the Standard Model (SESM), which can explain the dark matter as well as new physics anomalies such as the B physics anomalies and muon anomalous magnetic moment, etc. With the new scalar potential terms, we obtain the mass splittings for the real and imaginary parts of scalar fields. And thus we can have the DM co-annihilation process mediated by $Z$ boson, which couples exclusively to the CP-even and CP-odd parts of scalar fields. This is a brand new feature compared to the previous study. For the CP conserving case, we present the viable parameter space for the Higgs and $Z$ resonances, which can explain the B physics anomalies, muon anomalous magnetic moment, and dark matter relic density, as well as evade the constraint from the XENON1T direct detection simultaneously. For the CP-violating case, we consider the inelastic dark matter, and study four concrete scenarios for the inelastic DM-nucleon scatterings mediated by the Higgs and $Z$ bosons in details. Also, we present the benchmark points which satisfy the aforementioned constraints. Furthermore, we investigate the constraints from the dark matter-electron inelastic scattering processes mediated by the Higgs and $Z$ bosons in light of the XENONnT data. We show that the constraint on the $Z$ mediated process is weak, while the Higgs mediated process excludes the dark matter with mass around several MeV.Comment: 22 pages, 6 figures, 5 table

Jitter analysis of a superconducting nanowire single photon detector

Jitter is one of the key parameters for a superconducting nanowire single photon detector (SNSPD). Using an optimized time-correlated single photon counting system for jitter measurement, we extensively studied the dependence of system jitter on the bias current and working temperature. The signal-to-noise ratio of the single-photon-response pulse was proven to be an important factor in system jitter. The final system jitter was reduced to 18 ps by using a high-critical-current SNSPD, which showed an intrinsic SNSPD jitter of 15 ps. A laser ranging experiment using a 15-ps SNSPD achieved a record depth resolution of 3 mm at a wavelength of 1550 nm.Comment: 7 pages, 6 figure