arXiv subjects
Publications and source records attributed to Yi Huang.
We give an overview of the proof for Mirzakhani's volume recursion for the Weil-Petersson volumes of the moduli spaces of genus $g$ hyperbolic surfaces with $n$ labeled geodesic boundary components, and her application of this recursion to Witten's conjecture and the study of simple geodesic length spectrum growth rates.
It has been a great challenge to achieve the direct light manipulation of matter on a bulk scale. In this work, the direct light propulsion of matter was observed on a macroscopic scale for the first time using a bulk graphene based material. The unique structure and properties of graphene and the morphology of the bulk graphene material make it capable of not only absorbing light at various wavelengths but also emitting energetic electrons efficiently enough to drive the bulk material following Newtonian mechanics. Thus, the unique photonic and electronic properties of individual graphene sheets are manifested in the response of the bulk state. These results offer an exciting opportunity to bring about bulk scale light manipulation with the potential to realize long-sought proposals in areas such as the solar sail and space transportation driven directly by sunlight.
A new approach is introduced to significantly improve the performance of thermophotovoltaic (TPV) systems by using low-dimensional thermal emitters and photovoltaic (PV) cells. By reducing the thickness of both the emitter and the PV cell, strong spectral selectivity in both thermal emission and absorption can be achieved by confining photons in trapped waveguide modes inside the thin-films that act as thermal analogs to quantum wells. Simultaneously, photo-excited carriers travel shorter distances across the thin-films reducing bulk recombination losses resulting in a lower saturation current in the PV cell. We predict a TPV efficiency enhancement with near-field coupling between the thermal emitter and the PV cell of up to 38.7% using a germanium (Ge) emitter at 1000 K and a gallium antimonide (GaSb) cell with optimized thicknesses separated by 100 nm. Even in the far-field limit, the efficiency is predicted to reach 31.5%, which is an order of magnitude higher than the Shockley Queisser limit of 1.6% for a bulk GaSb cell and a blackbody emitter at 1000 K. The proposed design approach does not require nanoscale patterning of the emitter and PV cell surfaces, but instead offers a simple low-cost solution to improve the performance of a thermophotovoltaic system.
For large-scale discrete ill-posed problems, LSQR, a Lanczos bidiagonalization process based Krylov method, is most often used. It is well known that LSQR has natural regularizing properties, where the number of iterations plays the role of the regularization parameter. In this paper, for severely and moderately ill-posed problems, we establish quantitative bounds for the distance between the $k$-dimensional Krylov subspace and the subspace spanned by $k$ dominant right singular vectors. They show that the $k$-dimensional Krylov subspace may capture the $k$ dominant right singular vectors for severely and moderately ill-posed problems, but it seems not the case for mildly ill-posed problems. These results should be the first step towards to estimating the accuracy of the rank-$k$ approximation generated by Lanczos bidiagonalization. We also derive some other results, which help further understand the regularization effects of LSQR. We draw to a conclusion that a hybrid LSQR should generally be used for mildly ill-posed problems. We report numerical experiments to confirm our theory. We present more definitive and general observed phenomena, which will derive more research.
The action of the mapping class group of the thrice-punctured projective plane on its $\mathrm{GL}(2,\mathbb{C})$ character variety produces an algorithm for generating the simple length spectra of quasi-Fuchsian thrice-punctured projective planes. We apply this algorithm to quasi-Fuchsian representations of the corresponding fundamental group to prove: a sharp upper-bound for the length of its shortest geodesic, a McShane identity and the surprising result of non-polynomial growth for the number of simple closed geodesic lengths.
In this paper we define Clinical Data Intelligence as the analysis of data generated in the clinical routine with the goal of improving patient care. We define a science of a Clinical Data Intelligence as a data analysis that permits the derivation of scientific, i.e., generalizable and reliable results. We argue that a science of a Clinical Data Intelligence is sensible in the context of a Big Data analysis, i.e., with data from many patients and with complete patient information. We discuss that Clinical Data Intelligence requires the joint efforts of knowledge engineering, information extraction (from textual and other unstructured data), and statistics and statistical machine learning. We describe some of our main results as conjectures and relate them to a recently funded research project involving two major German university hospitals.
In this paper, we investigate the optimal energy efficient coordinated beamforming in multi-cell multiple-input single-output (MISO) systems with $K$ multiple-antenna base stations (BS) and $K$ single-antenna mobile stations (MS), where each BS sends information to its own intended MS with cooperatively designed transmit beamforming. We assume single user detection at the MS by treating the interference as noise. By taking into account a realistic power model at the BS, we characterize the Pareto boundary of the achievable energy efficiency (EE) region of the $K$ links, where the EE of each link is defined as the achievable data rate at the MS divided by the total power consumption at the BS. Since the EE of each link is non-cancave (which is a non-concave function over an affine function), characterizing this boundary is difficult. To meet this challenge, we relate this multi-cell MISO system to cognitive radio (CR) MISO channels by applying the concept of interference temperature (IT), and accordingly transform the EE boundary characterization problem into a set of fractional concave programming problems. Then, we apply the fractional concave programming technique to solve these fractional concave problems, and correspondingly give a parametrization for the EE boundary in terms of IT levels. Based on this characterization, we further present a decentralized algorithm to implement the multi-cell coordinated beamforming, which is shown by simulations to achieve the EE Pareto boundary.
In this paper, we introduce a new scale of tent spaces which covers, the (weighted) tent spaces of Coifman-Meyer-Stein and of Hofmann-Mayboroda-McIntosh, and some other tent spaces considered by Dahlberg, Kenig-Pipher and Auscher-Axelsson in elliptic equations. The strong factorizations within our tent spaces, with applications to quasi-Banach complex interpolation and to multiplier-duality theory, are established. This way, we unify and extend the corresponding results obtained by Coifman-Meyer-Stein, Cohn-Verbitsky and Hytönen-Rosén.
We prove a McShane-type identity - a series, expressed in terms of geodesic lengths, that sums to 2πfor any closed hyperbolic surface with one distinguished point. To do so, we prove a generalized Birman-Series theorem showing that the set of complete geodesics on a hyperbolic surface with large cone angles is sparse.
High speed downlink packet access (HSDPA) has been successfully applied in commercial systems and improves user experience significantly. However, it incurs substantial energy consumption. In this paper, we address this issue by proposing a novel energy efficient semi-static power control and link adaptation scheme in HSDPA. Through estimating the EE under different modulation and coding schemes (MCSs) and corresponding transmit power, the proposed scheme can determine the most energy efficient MCS level and transmit power at the Node B. And then the Node B configure the optimal MCS level and transmit power. In order to decrease the signaling overhead caused by the configuration, a dual trigger mechanism is employed. After that, we extend the proposed scheme to the multiple input multiple output (MIMO) scenarios. Simulation results confirm the significant EE improvement of our proposed scheme. Finally, we give a discussion on the potential EE gain and challenge of the energy efficient mode switching between single input multiple output (SIMO) and MIMO configuration in HSDPA.
The time-varying feature of wireless channels usually makes the hard delay bound for data transmissions unrealistic to guarantee. In contrast, the statistically-bounded delay with a small violation probability has been widely used for delay quality-of-service (QoS) characterization and evaluation. While existing research mainly focused on the statistical-delay control in single-hop links, in this paper we propose the QoS-driven power-allocation scheme over two-hop wireless relay links to statistically upper-bound the end-to-end delay under the decodeand- forward (DF) relay transmissions. Specifically, by applying the effective capacity and effective bandwidth theories, we first analyze the delay-bound violation probability over two tops each with independent service processes. Then, we show that an efficient approach for statistical-delay guarantees is to make the delay distributions of both hops identical, which, however, needs to be obtained through asymmetric resource allocations over the two hops. Motivated by this fact, we formulate and solve an optimization problem aiming at minimizing the average power consumptions to satisfy the specified end-to-end delay-bound violation probability over two-hop relay links. Also conducted is a set of simulations results to show the impact of the QoS requirements, traffic load, and position of the relay node on the power allocation under our proposed optimal scheme.