arXiv subjects

Wei Fu

Publications and source records attributed to Wei Fu.

At least 55 records · Page 3Linked to original sources

arXiv2020

High-acoustic-index-contrast phononic circuits: numerical modeling

We numerically model key building blocks of a phononic integrated circuit that enable phonon routing in high-acoustic-index waveguides. Our particular focus is on Gallium Nitride-on-sapphire phononic platform which has recently demonstrated high acoustic confinement in its top layer without the use of suspended structures. We start with systematic simulation of various transverse phonon modes supported in strip waveguides and ring resonators with sub-wavelength cross-section. Mode confinement and quality factors of phonon modes are numerically investigated with respect to geometric parameters. Quality factor up to $10^{8}$ is predicted in optimized ring resonators. We next study the design of the phononic directional couplers, and present key design parameters for achieving strong evanescent couplings between modes propagating in parallel waveguides. Last, interdigitated transducer electrodes are included in the simulation for direct excitation of a ring resonator and critical coupling between microwave input and phononic dissipation. Our work provides comprehensive numerical characterization of phonon modes and functional phononic components in high-acoustic-index phononic circuits, which supplements previous theories and contributes to the emerging field of phononic integrated circuits.

physics.app-ph↗

arXiv2020

Ground-state Pulsed Cavity Electro-optics for Microwave-to-optical Conversion

In the development of quantum microwave-to-optical (MO) converters, excessive noise induced by the parametric optical drive remains a major challenge at milli-Kelvin temperatures. Here we study the extraneous noise added to an electro-optic transducer in its quantum ground state under an intense pulsed optical excitation. The integrated electro-optical transducer leverages the inherent Pockels effect of aluminum nitride microrings, flip-chip bonded to a superconducting resonator. Applying a pulsed optical drive with peak power exceeding the cooling power of the dilution refrigerator at its base temperature, we observe efficient bi-directional MO conversion, with near-ground state microwave thermal excitation ($\bar{n}_\mathrm{e}=0.09\pm0.06$). Time evolution study reveals that the residual thermal excitation is dominated by the superconductor absorption of stray light scattered off the chip-fiber interface. Our results shed light on suppressing microwave noise in a cavity electro-optic system under intense optical drive, which is an essential step towards quantum state transduction between microwave and optical frequencies.

quant-ph↗

arXiv2020

Direct linearisation approach to discrete integrable systems associated with $\mathbb{Z}_\mathcal{N}$ graded Lax pairs

Fordy and Xenitidis [J. Phys. A: Math. Theor. 50 (2017) 165205] recently proposed a large class of discrete integrable systems which include a number of novel integrable difference equations, from the perspective of $\mathbb{Z}_\mathcal{N}$ graded Lax pairs, without providing solutions. In this paper, we establish the link between the Fordy-Xenitidis discrete systems in coprime case and linear integral equations in certain form, which reveals solution structure of these equations. The bilinear form of the Fordy-Xenitidis integrable difference equations is also presented together with the associated general tau function. Furthermore, the solution structure explains the connections between the Fordy-Xenitidis novel models and the discrete Gel'fand-Dikii hierarchy.

nlin.SI↗

arXiv2020

Cavity piezo-mechanics for superconducting-nanophotonic quantum interface

Hybrid quantum systems are essential for the realization of distributed quantum networks. In particular, piezo-mechanics operating at typical superconducting qubit frequencies features low thermal excitations, and offers an appealing platform to bridge superconducting quantum processors and optical telecommunication channels. However, integrating superconducting and optomechanical elements at cryogenic temperatures with sufficiently strong interactions remains a tremendous challenge. Here, we report an integrated superconducting cavity piezo-optomechanical platform where 10-GHz phonons are resonantly coupled with photons in a superconducting and a nanophotonic cavities at the same time. Benefited from the achieved large piezo-mechanical cooperativity ($C_\mathrm{em}\sim7$) and the enhanced optomechanical coupling boosted by a pulsed optical pump, we demonstrate coherent interactions at cryogenic temperatures via the observation of efficient microwave-optical photon conversion. This hybrid interface makes a substantial step towards quantum communication at large scale, as well as novel explorations in microwave-optical photon entanglement and quantum sensing mediated by gigahertz phonons.

physics.optics↗

arXiv2019

How to "DODGE" Complex Software Analytics?

Machine learning techniques applied to software engineering tasks can be improved by hyperparameter optimization, i.e., automatic tools that find good settings for a learner's control parameters. We show that such hyperparameter optimization can be unnecessarily slow, particularly when the optimizers waste time exploring "redundant tunings"', i.e., pairs of tunings which lead to indistinguishable results. By ignoring redundant tunings, DODGE, a tuning tool, runs orders of magnitude faster, while also generating learners with more accurate predictions than seen in prior state-of-the-art approaches.

cs.SE↗

arXiv2019

Polarization mode hybridization and conversion in phononic wire waveguides

Phononic wire waveguides of subwavelength cross-section support two orthogonal polarization modes: the out-of-plane motion dominated Rayleigh-like and the in-plane motion dominated Love-like modes, analogous to transverse-electric and transverse-magnetic modes in photonic waveguides. Due to the anisotropic elasticity of the substrate material, the polarization states of phonons propagating along certain crystallographic orientations can strongly hybridize. Here we experimentally investigate the orientation-dependent mode hybridization in phononic wire waveguides patterned from GaN-on-sapphire thin films. Such mode hybridization allows efficient actuation of piezoelectrically inactive Love-like modes using common interdigital electrodes designed for Rayleigh-like modes, and further enables on-chip polarization conversion between guided transverse modes. Both are important for on-chip implementation of complex phononic circuits.

physics.app-ph↗

arXiv2019

Radiative cooling of a superconducting resonator

Cooling microwave resonators to near the quantum ground state, crucial for their operation in the quantum regime, is typically achieved by direct device refrigeration to a few tens of millikelvin. However, in quantum experiments that require high operation power such as microwave-to-optics quantum transduction, it is desirable to operate at higher temperatures with non-negligible environmental thermal excitations, where larger cooling power is available. In this Letter, we present a radiative cooling protocol to prepare a superconducting microwave mode near its quantum ground state in spite of warm environment temperatures for the resonator. In this proof-of-concept experiment, the mode occupancy of a 10-GHz superconducting resonator thermally anchored at 1.02~K is reduced to $0.44\pm0.05$ by radiatively coupling to a 70-mK cold load. This radiative cooling scheme allows high-operation-power microwave experiments to work in the quantum regime, and opens possibilities for routing microwave quantum states to elevated temperatures.

quant-ph↗

arXiv2019

Quantum Microwave Radiometry with a Superconducting Qubit

The interaction of photons and coherent quantum systems can be employed to detect electromagnetic radiation with remarkable sensitivity. We introduce a quantum radiometer based on the photon-induced-dephasing process of a superconducting qubit for sensing microwave radiation at the sub-unit-photon level. Using this radiometer, we demonstrated the radiative cooling of a 1-K microwave resonator and measured its mode temperature with an uncertainty ~0.01 K. We have thus developed a precise tool for studying the thermodynamics of quantum microwave circuits, which provides new solutions for calibrating hybrid quantum systems and detecting candidate particles for dark matter.

quant-ph↗

arXiv2019

Heralded Generation and Detection of Entangled Microwave--Optical Photon Pairs

Quantum state transfer between microwave and optical frequencies is essential for connecting superconducting quantum circuits to coherent optical systems and extending microwave quantum networks over long distances. To build such a hybrid `quantum Internet,' an important experiment in the quantum regime is to entangle microwave and optical modes. Based on the model of a generic cavity electro-optomechanical system, we present a heralded scheme to generate entangled microwave--optical photon pairs, which can bypass the efficiency threshold for quantum channel capacity in direct transfer protocols. The parameter regime for entanglement verification is identified that is compatible with realistic experimental settings. Our scheme is feasible given the latest experimental progress on electro-optomechanics, and can be potentially generalized to various physical systems.

quant-ph↗

arXiv2018

Linear integral equations, infinite matrices, and soliton hierarchies

A systematic framework is presented for the construction of hierarchies of soliton equations. This is realised by considering scalar linear integral equations and their representations in terms of infinite matrices, which give rise to all (2+1)- and (1+1)-dimensional soliton hierarchies associated with scalar differential spectral problems. The integrability characteristics for the obtained soliton hierarchies, including Miura-type transforms, $τ$-functions, Lax pairs as well as soliton solutions, are also derived within this framework.

nlin.SI↗

arXiv2018

Direct linearisation of the discrete-time two-dimensional Toda lattices

The discrete-time two-dimensional Toda lattice of $A_\infty$-type is studied within the direct linearisation framework, which allows us to deal with several nonlinear equations in this class simultaneously and to construct more general solutions of these equations. The periodic reductions of this model are also considered, giving rise to the discrete-time two-dimensional Toda lattices of $A_{r-1}^{(1)}$-type for $r\geq 2$ (which amount to the negative flows of members in the discrete Gel'fand--Dikii hierarchy) and their integrability properties.

nlin.SI↗

arXiv2018

Data-Driven Search-based Software Engineering

This paper introduces Data-Driven Search-based Software Engineering (DSE), which combines insights from Mining Software Repositories (MSR) and Search-based Software Engineering (SBSE). While MSR formulates software engineering problems as data mining problems, SBSE reformulates SE problems as optimization problems and use meta-heuristic algorithms to solve them. Both MSR and SBSE share the common goal of providing insights to improve software engineering. The algorithms used in these two areas also have intrinsic relationships. We, therefore, argue that combining these two fields is useful for situations (a) which require learning from a large data source or (b) when optimizers need to know the lay of the land to find better solutions, faster. This paper aims to answer the following three questions: (1) What are the various topics addressed by DSE? (2) What types of data are used by the researchers in this area? (3) What research approaches do researchers use? The paper briefly sets out to act as a practical guide to develop new DSE techniques and also to serve as a teaching resource. This paper also presents a resource (tiny.cc/data-se) for exploring DSE. The resource contains 89 artifacts which are related to DSE, divided into 13 groups such as requirements engineering, software product lines, software processes. All the materials in this repository have been used in recent software engineering papers; i.e., for all this material, there exist baseline results against which researchers can comparatively assess their new ideas.

cs.SE↗

arXiv2018

Building Better Quality Predictors Using "$ε$-Dominance"

Despite extensive research, many methods in software quality prediction still exhibit some degree of uncertainty in their results. Rather than treating this as a problem, this paper asks if this uncertainty is a resource that can simplify software quality prediction. For example, Deb's principle of $ε$-dominance states that if there exists some $ε$ value below which it is useless or impossible to distinguish results, then it is superfluous to explore anything less than $ε$. We say that for "large $ε$ problems", the results space of learning effectively contains just a few regions. If many learners are then applied to such large $ε$ problems, they would exhibit a "many roads lead to Rome" property; i.e., many different software quality prediction methods would generate a small set of very similar results. This paper explores DART, an algorithm especially selected to succeed for large $ε$ software quality prediction problems. DART is remarkable simple yet, on experimentation, it dramatically out-performs three sets of state-of-the-art defect prediction methods. The success of DART for defect prediction begs the questions: how many other domains in software quality predictors can also be radically simplified? This will be a fruitful direction for future work.

cs.SE↗

arXiv2018

Applications of Psychological Science for Actionable Analytics

Actionable analytics are those that humans can understand, and operationalize. What kind of data mining models generate such actionable analytics? According to psychological scientists, humans understand models that most match their own internal models, which they characterize as lists of "heuristic" (i.e., lists of very succinct rules). One such heuristic rule generator is the Fast-and-Frugal Trees (FFT) preferred by psychological scientists. Despite their successful use in many applied domains, FFTs have not been applied in software analytics. Accordingly, this paper assesses FFTs for software analytics. We find that FFTs are remarkably effective. Their models are very succinct (5 lines or less describing a binary decision tree). These succinct models outperform state-of-the-art defect prediction algorithms defined by Ghortra et al. at ICSE'15. Also, when we restrict training data to operational attributes (i.e., those attributes that are frequently changed by developers), FFTs perform much better than standard learners. Our conclusions are two-fold. Firstly, there is much that software analytics community could learn from psychological science. Secondly, proponents of complex methods should always baseline those methods against simpler alternatives. For example, FFTs could be used as a standard baseline learner against which other software analytics tools are compared.

cs.SE↗

arXiv2018

What is Wrong with Topic Modeling? (and How to Fix it Using Search-based Software Engineering)

Context: Topic modeling finds human-readable structures in unstructured textual data. A widely used topic modeler is Latent Dirichlet allocation. When run on different datasets, LDA suffers from "order effects" i.e. different topics are generated if the order of training data is shuffled. Such order effects introduce a systematic error for any study. This error can relate to misleading results;specifically, inaccurate topic descriptions and a reduction in the efficacy of text mining classification results. Objective: To provide a method in which distributions generated by LDA are more stable and can be used for further analysis. Method: We use LDADE, a search-based software engineering tool that tunes LDA's parameters using DE (Differential Evolution). LDADE is evaluated on data from a programmer information exchange site (Stackoverflow), title and abstract text of thousands ofSoftware Engineering (SE) papers, and software defect reports from NASA. Results were collected across different implementations of LDA (Python+Scikit-Learn, Scala+Spark); across different platforms (Linux, Macintosh) and for different kinds of LDAs (VEM,or using Gibbs sampling). Results were scored via topic stability and text mining classification accuracy. Results: In all treatments: (i) standard LDA exhibits very large topic instability; (ii) LDADE's tunings dramatically reduce cluster instability; (iii) LDADE also leads to improved performances for supervised as well as unsupervised learning. Conclusion: Due to topic instability, using standard LDA with its "off-the-shelf" settings should now be depreciated. Also, in future, we should require SE papers that use LDA to test and (if needed) mitigate LDA topic instability. Finally, LDADE is a candidate technology for effectively and efficiently reducing that instability.

cs.SE↗

arXiv2018

500+ Times Faster Than Deep Learning (A Case Study Exploring Faster Methods for Text Mining StackOverflow)

Deep learning methods are useful for high-dimensional data and are becoming widely used in many areas of software engineering. Deep learners utilizes extensive computational power and can take a long time to train-- making it difficult to widely validate and repeat and improve their results. Further, they are not the best solution in all domains. For example, recent results show that for finding related Stack Overflow posts, a tuned SVM performs similarly to a deep learner, but is significantly faster to train. This paper extends that recent result by clustering the dataset, then tuning very learners within each cluster. This approach is over 500 times faster than deep learning (and over 900 times faster if we use all the cores on a standard laptop computer). Significantly, this faster approach generates classifiers nearly as good (within 2\% F1 Score) as the much slower deep learning method. Hence we recommend this faster methods since it is much easier to reproduce and utilizes far fewer CPU resources. More generally, we recommend that before researchers release research results, that they compare their supposedly sophisticated methods against simpler alternatives (e.g applying simpler learners to build local models).

cs.SE↗

arXiv2018

High Quality Factor Surface Fabry-Perot Cavity of Acoustic Waves

Surface acoustic wave (SAW) resonators are critical components in wireless communications and many sensing applications. They have also recently emerged as subject of study in quantum acoustics at the single phonon level. Acoustic loss reduction and mode confinement are key performance factors in SAW resonators. Here we report the design and experimental realization of a high quality factor Fabry-Perot SAW resonators formed in between tapered phononic crystal mirrors patterned on a GaN-on-sapphire material platform . The fabricated SAW resonators are characterized by both electrical network analyzer and optical heterodyne vibrometer. We observed standing Rayleigh wave inside the cavity, with an intrinsic quality factor exceeding 13,000 at ambient conditions.

physics.app-ph↗

arXiv2017

On reductions of the discrete Kadomtsev--Petviashvili-type equations

The reduction by restricting the spectral parameters $k$ and $k'$ on a generic algebraic curve of degree $\mathcal{N}$ is performed for the discrete AKP, BKP and CKP equations, respectively. A variety of two-dimensional discrete integrable systems possessing a more general solution structure arise from the reduction, and in each case a unified formula for generic positive integer $\mathcal{N}\geq 2$ is given to express the corresponding reduced integrable lattice equations. The obtained extended two-dimensional lattice models give rise to many important integrable partial difference equations as special degenerations. Some new integrable lattice models such as the discrete Sawada--Kotera, Kaup--Kupershmidt and Hirota--Satsuma equations in extended form are given as examples within the framework.

nlin.SI↗