arXiv subjects

Luo

Publications and source records attributed to Luo.

9 recordsLinked to original sources

arXiv2025

Amplitude-Domain Reflection Modulation for Active RIS-Assisted Wireless Communications

In this paper, we propose a novel active reconfigurable intelligent surface (RIS)-assisted amplitude-domain reflection modulation (ADRM) transmission scheme, termed as ARIS-ADRM. This innovative approach leverages the additional degree of freedom (DoF) provided by the amplitude domain of the active RIS to perform index modulation (IM), thereby enhancing spectral efficiency (SE) without increasing the costs associated with additional radio frequency (RF) chains. Specifically, the ARIS-ADRM scheme transmits information bits through both the modulation symbol and the index of active RIS amplitude allocation patterns (AAPs). To evaluate the performance of the proposed ARIS-ADRM scheme, we provide an achievable rate analysis and derive a closed-form expression for the upper bound on the average bit error probability (ABEP). Furthermore, we formulate an optimization problem to construct the AAP codebook, aiming to minimize the ABEP. Simulation results demonstrate that the proposed scheme significantly improves error performance under the same SE conditions compared to its benchmarks. This improvement is due to its ability to flexibly adapt the transmission rate by fully exploiting the amplitude domain DoF provided by the active RIS.

eess.SP↗

arXiv2021

Traders in a Strange Land: Agent-based discrete-event market simulation of the Figgie card game

Figgie is a card game that approximates open-outcry commodities trading. We design strategies for Figgie and study their performance and the resulting market behavior. To do this, we develop a flexible agent-based discrete-event market simulation in which agents operating under our strategies can play Figgie. Our simulation builds upon previous work by simulating latencies between agents and the market in a novel and efficient way. The fundamentalist strategy we develop takes advantage of Figgie's unique notion of asset value, and is, on average, the profit-maximizing strategy in all combinations of agent strategies tested. We develop a strategy, the "bottom-feeder", which estimates value by observing orders sent by other agents, and find that it limits the success of fundamentalists. We also find that chartist strategies implemented, including one from the literature, fail by going into feedback loops in the small Figgie market. We further develop a bootstrap method for statistically comparing strategies in a zero-sum game. Our results demonstrate the wide-ranging applicability of agent-based discrete-event simulations in studying markets.

q-fin.TR↗

arXiv2020

RustViz: Interactively Visualizing Ownership and Borrowing

Rust is a systems programming language that guarantees memory safety without the need for a garbage collector by statically tracking ownership and borrowing events. The associated rules are subtle and unique among industry programming languages, which can make learning Rust more challenging. Motivated by the challenges that Rust learners face, we are developing RustViz, a tool that allows teachers to generate an interactive timeline depicting ownership and borrowing events for each variable in a Rust code example. These visualizations are intended to help Rust learners develop an understanding of ownership and borrowing by example. This paper introduces RustViz by example, shows how teachers can use it to generate visualizations, describes learning goals, and proposes a study designed to evaluate RustViz based on these learning goals.

cs.PL↗

arXiv2019

Linear Multiple Low-Rank Kernel Based Stationary Gaussian Processes Regression for Time Series

Gaussian processes (GP) for machine learning have been studied systematically over the past two decades and they are by now widely used in a number of diverse applications. However, GP kernel design and the associated hyper-parameter optimization are still hard and to a large extend open problems. In this paper, we consider the task of GP regression for time series modeling and analysis. The underlying stationary kernel can be approximated arbitrarily close by a new proposed grid spectral mixture (GSM) kernel, which turns out to be a linear combination of low-rank sub-kernels. In the case where a large number of the sub-kernels are used, either the Nystr\"{o}m or the random Fourier feature approximations can be adopted to deal efficiently with the computational demands. The unknown GP hyper-parameters consist of the non-negative weights of all sub-kernels as well as the noise variance; their estimation is performed via the maximum-likelihood (ML) estimation framework. Two efficient numerical optimization methods for solving the unknown hyper-parameters are derived, including a sequential majorization-minimization (MM) method and a non-linearly constrained alternating direction of multiplier method (ADMM). The MM matches perfectly with the proven low-rank property of the proposed GSM sub-kernels and turns out to be a part of efficiency, stable, and efficient solver, while the ADMM has the potential to generate better local minimum in terms of the test MSE. Experimental results, based on various classic time series data sets, corroborate that the proposed GSM kernel-based GP regression model outperforms several salient competitors of similar kind in terms of prediction mean-squared-error and numerical stability.

cs.LG↗

arXiv2018

Room Temperature Intrinsic Ferromagnetism in Epitaxial Manganese Selenide Films in the Monolayer Limit

Monolayer van der Waals (vdW) magnets provide an exciting opportunity for exploring two-dimensional (2D) magnetism for scientific and technological advances, but the intrinsic ferromagnetism has only been observed at low temperatures. Here, we report the observation of room temperature ferromagnetism in manganese selenide (MnSe$_x$) films grown by molecular beam epitaxy (MBE). Magnetic and structural characterization provides strong evidence that in the monolayer limit, the ferromagnetism originates from a vdW manganese diselenide (MnSe$_2$) monolayer, while for thicker films it could originate from a combination of vdW MnSe$_2$ and/or interfacial magnetism of $\alpha$-MnSe(111). Magnetization measurements of monolayer MnSe$_x$ films on GaSe and SnSe$_2$ epilayers show ferromagnetic ordering with large saturation magnetization of ~ 4 Bohr magnetons per Mn, which is consistent with density functional theory calculations predicting ferromagnetism in monolayer 1T-MnSe$_2$. Growing MnSe$_x$ films on GaSe up to high thickness (~ 40 nm) produces $\alpha$-MnSe(111), and an enhanced magnetic moment (~ 2x) compared to the monolayer MnSe$_x$ samples. Detailed structural characterization by scanning transmission electron microscopy (STEM), scanning tunneling microscopy (STM), and reflection high energy electron diffraction (RHEED) reveal an abrupt and clean interface between GaSe(0001) and $\alpha$-MnSe(111). In particular, the structure measured by STEM is consistent with the presence of a MnSe$_2$ monolayer at the interface. These results hold promise for potential applications in energy efficient information storage and processing.

cond-mat.mtrl-sci↗

arXiv2017

Opto-Valleytronic Spin Injection in Monolayer MoS2/Few-Layer Graphene Hybrid Spin Valves

Two dimensional (2D) materials provide a unique platform for spintronics and valleytronics due to the ability to combine vastly different functionalities into one vertically-stacked heterostructure, where the strengths of each of the constituent materials can compensate for the weaknesses of the others. Graphene has been demonstrated to be an exceptional material for spin transport at room temperature, however it lacks a coupling of the spin and optical degrees of freedom. In contrast, spin/valley polarization can be efficiently generated in monolayer transition metal dichalcogenides (TMD) such as MoS2 via absorption of circularly-polarized photons, but lateral spin or valley transport has not been realized at room temperature. In this letter, we fabricate monolayer MoS2/few-layer graphene hybrid spin valves and demonstrate, for the first time, the opto-valleytronic spin injection across a TMD/graphene interface. We observe that the magnitude and direction of spin polarization is controlled by both helicity and photon energy. In addition, Hanle spin precession measurements confirm optical spin injection, spin transport, and electrical detection up to room temperature. Finally, analysis by a one-dimensional drift-diffusion model quantifies the optically injected spin current and the spin transport parameters. Our results demonstrate a 2D spintronic/valleytronic system that achieves optical spin injection and lateral spin transport at room temperature in a single device, which paves the way for multifunctional 2D spintronic devices for memory and logic applications.

cond-mat.mes-hall↗

arXiv2016

Imaging Spin Dynamics in Monolayer WS2 by Time-Resolved Kerr Rotation Microscopy

Monolayer transition metal dichalcogenides (TMD) have immense potential for future spintronic and valleytronic applications due to their two-dimensional nature and long spin/valley lifetimes. We investigate the origin of these long-lived states in n-type WS2 using time-resolved Kerr rotation microscopy and photoluminescence microscopy with ~1 micron spatial resolution. Comparing the spatial dependence of the Kerr rotation signal and the photoluminescence reveals a correlation with neutral exciton emission, which is likely due to the transfer of angular momentum to resident conduction electrons with long spin/valley lifetimes. In addition, we observe an unexpected anticorrelation between the Kerr rotation and trion emission, which provides evidence for the presence of long-lived spin/valley-polarized dark trions. We also find that the spin/valley polarization in WS2 is robust to magnetic fields up to 700 mT, indicative of spins and valleys that are stabilized with strong spin-orbit fields.

cond-mat.mes-hall↗

arXiv2011

Quantum Shock Waves and Domain Walls in the Real-Time Dynamics of a Superfluid Unitary Fermi Gas

We show that in the collision of two superfluid fermionic atomic clouds one observes the formation of quantum shock waves as discontinuities in the number density and collective flow velocity. Domain walls, which are topological excitations of the superfluid order parameter, are also generated and exhibit abrupt phase changes by $\pi$ and slower motion than the shock waves. The domain walls are distinct from the gray soliton train or number density ripples formed in the wake of the shock waves and observed in the collisions of superfluid bosonic atomic clouds. Domain walls with opposite phase jumps appear to collide elastically.

cond-mat.quant-gas↗

arXiv2010

Generation and Dynamics of Quantized Vortices in a Unitary Fermi Superfluid

Superfluidity and superconductivity are remarkable manifestations of quantum coherence at a macroscopic scale. The dynamics of superfluids has dominated the study of these systems for decades now, but a comprehensive theoretical framework is still lacking. We introduce a local extension of the time-dependent density functional theory to describe the dynamics of fermionic superfluids. Within this approach one can correctly represent vortex quantization, generation, and dynamics, the transition from a superfluid to a normal phase and a number of other large amplitude collective modes which are beyond the scope of two-fluid hydrodynamics, Ginzburg-Landau and/or Gross-Pitaevskii approaches. We illustrate the power of this approach by studying the generation of quantized vortices, vortex rings, vortex reconnection, and transition from a superfluid to a normal state in real time for a unitary Fermi gas. We predict the emergence of a new qualitative phenomenon in superfluid dynamics of gases, the existence of stable superfluidity when the systems are stirred with velocities significantly exceeding the nominal Landau critical velocity in these systems.

cond-mat.quant-gas↗