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We propose a circuit architecture for a dissipatively error-corrected GKP qubit. The device consists of a high-impedance LC circuit coupled to a Josephson junction and a resistor via a controllable switch. When the switch is activated via a particular family of stepwise protocols, the resistor absorbs all noise-induced entropy, resulting in dissipative error correction of both phase and amplitude errors. This leads to an exponential increase of qubit lifetime, reaching beyond 10ms in simulations with near-feasible parameters. We show that the lifetime remains exponentially long in the presence of extrinsic noise and device/control imperfections (e.g., due to parasitics and finite control bandwidth) under specific thresholds. In this regime, lifetime is likely only limited by phase slips and quasiparticle tunneling. We show that the qubit can be read out and initialized via measurement of the supercurrent in the Josephson junction. We finally show that the qubit supports native self-correcting single-qubit Clifford gates, where dissipative error-correction of control noise leads to exponential suppression of gate infidelity., Comment: 12 pages + 8 figures in the main text

Identifying and measuring the "localization length'' in many-body systems in the vicinity of a many-body localization transition is difficult. Following Hatano and Nelson, a recent work (Heuben, White, Refael, PRB 103, 064201 (2021)) introduced an "imaginary vector potential'' to a disordered ring of interacting fermions, in order to define a many-body localization length (corresponding, in the non-interacting case, to the end-to-end Green's function of the hermitian system). We extend these results, by connecting this localization length to the length scale appearing in the avalanche model of delocalization. We use this connection to derive the distribution of the localization length at the MBL transition, finding good agreement with our numerical observations. Our results demonstrate how a localization length defined as such probes the localization of the underlying ring, without the need to explicitly construct the l-bits., Comment: 24 pages (12 main text + 12 appendices/references), 21 Figures. v3 contains final version

Long-range ordering is typically associated with a decrease in entropy. Yet, it can also be driven by increasing entropy in certain special cases. We demonstrate that artificial spin ice arrays of single-domain nanomagnets can be designed to produce entropy-driven order. We focus on the tetris artificial spin ice structure, a highly frustrated array geometry with a zero-point Pauli entropy, which is formed by selectively creating regular vacancies on the canonical square ice lattice. We probe thermally active tetris artificial spin ice both experimentally and through simulations, measuring the magnetic moments of the individual nanomagnets. We find two-dimensional magnetic ordering in one subset of these moments, which we demonstrate to be induced by disorder (i.e., increased entropy) in another subset of the moments. In contrast with other entropy-driven systems, the discrete degrees of freedom in tetris artificial spin ice are binary and are both designable and directly observable at the microscale, and the entropy of the system is precisely calculable in simulations. This example, in which the system's interactions and ground state entropy are well-defined, expands the experimental landscape for the study of entropy-driven ordering., Comment: 53 pages, 19 figures (including Supplementary Information)

One-dimensional strings of local excitations are a fascinating feature of the physical behavior of strongly correlated topological quantum matter. Here we study strings of local excitations in a classical system of interacting nanomagnets, the Santa Fe Ice geometry of artificial spin ice. We measured the moment configuration of the nanomagnets, both after annealing near the ferromagnetic Curie point and in a thermally dynamic state. While the Santa Fe Ice lattice structure is complex, we demonstrate that its disordered magnetic state is naturally described within a framework of emergent strings. We show experimentally that the string length follows a simple Boltzmann distribution with an energy scale that is associated with the system's magnetic interactions and is consistent with theoretical predictions. The results demonstrate that string description and associated topological characteristics are not unique to quantum models but can also provide a simplifying description of complex classical systems with non-trivial frustration., Comment: 46 pages including SI

We study the instantons describing the production of particles at the ends of codimension-one objects (strings and struts) in $(2+1)$-dimensional Minkowski and de Sitter spaces. A Minkowskian background allows only for systems with vanishing total mass, so that either negative mass particles or negative tension struts are required. On a de Sitter background, on the other hand, we find processes describing the production of string/particle systems with no negative energies involved. We also compute the probabilities of creating and of breaking an infinite cosmic string in de Sitter space. We perform our analysis of the system in de Sitter space employing a generalization of the toroidal coordinate system to the three-sphere., Comment: 13 pages, 4 figures

Serious games are beneficial for education in various computer science areas. Numerous works have reported the experiences of using games (not only playing but also development) in teaching and learning. Considering it could be difficult for teachers/students to prepare/develop a game from scratch during one semester, assistant educational materials would be crucial in the corresponding courses. Unfortunately, the literature shows that not many materials from educational game projects are shared. To help different educators identify suitable courseware and help students implement game development, it is worth further investigating and accumulating the educational resources from individual game projects. Following such an idea, this paper proposes a game development project of an object-oriented Sokoban solver, and exposes relevant educational materials. The documented system design can be viewed as a ready-to-use resource for education in object-oriented analysis and design (OOAD), while the Sokoban solver itself may be used as an assignment platform for teaching artificial intelligence (AI). Further documentation, platform, and APIs will be realized and shared in the future to facilitate others' educational activities. Overall, this work is supposed to inspire and encourage other researchers and educators to post available materials of more game projects for the purpose of sharing and reuse., Comment: Proceedings of the 44th Annual Frontiers in Education Conference (FIE 2014), pp. 1-4, Madrid, Spain, October 22-25, 2014

Software engineering considers performance evaluation to be one of the key portions of software quality assurance. Unfortunately, there seems to be a lack of standard methodologies for performance evaluation even in the scope of experimental computer science. Inspired by the concept of "instantiation" in object-oriented programming, we distinguish the generic performance evaluation logic from the distributed and ad-hoc relevant studies, and develop an abstract evaluation methodology (by analogy of "class") we name Domain Knowledge-driven Methodology (DoKnowMe). By replacing five predefined domain-specific knowledge artefacts, DoKnowMe could be instantiated into specific methodologies (by analogy of "object") to guide evaluators in performance evaluation of different software and even computing systems. We also propose a generic validation framework with four indicators (i.e.~usefulness, feasibility, effectiveness and repeatability), and use it to validate DoKnowMe in the Cloud services evaluation domain. Given the positive and promising validation result, we plan to integrate more common evaluation strategies to improve DoKnowMe and further focus on the performance evaluation of Cloud autoscaler systems.

Background: Cloud Computing is increasingly booming in industry with many competing providers and services. Accordingly, evaluation of commercial Cloud services is necessary. However, the existing evaluation studies are relatively chaotic. There exists tremendous confusion and gap between practices and theory about Cloud services evaluation. Aim: To facilitate relieving the aforementioned chaos, this work aims to synthesize the existing evaluation implementations to outline the state-of-the-practice and also identify research opportunities in Cloud services evaluation. Method: Based on a conceptual evaluation model comprising six steps, the Systematic Literature Review (SLR) method was employed to collect relevant evidence to investigate the Cloud services evaluation step by step. Results: This SLR identified 82 relevant evaluation studies. The overall data collected from these studies essentially represent the current practical landscape of implementing Cloud services evaluation, and in turn can be reused to facilitate future evaluation work. Conclusions: Evaluation of commercial Cloud services has become a world-wide research topic. Some of the findings of this SLR identify several research gaps in the area of Cloud services evaluation (e.g., the Elasticity and Security evaluation of commercial Cloud services could be a long-term challenge), while some other findings suggest the trend of applying commercial Cloud services (e.g., compared with PaaS, IaaS seems more suitable for customers and is particularly important in industry). This SLR study itself also confirms some previous experiences and reveals new Evidence-Based Software Engineering (EBSE) lessons.

Benchmark suites are significant for evaluating various aspects of Cloud services from a holistic view. However, there is still a gap between using benchmark suites and achieving holistic impression of the evaluated Cloud services. Most Cloud service evaluation work intended to report individual benchmarking results without delivering summary measures. As a result, it could be still hard for customers with such evaluation reports to understand an evaluated Cloud service from a global perspective. Inspired by the boosting approaches to machine learning, we proposed the concept Boosting Metrics to represent all the potential approaches that are able to integrate a suite of benchmarking results. This paper introduces two types of preliminary boosting metrics, and demonstrates how the boosting metrics can be used to supplement primary measures of individual Cloud service features. In particular, boosting metrics can play a summary Response role in applying experimental design to Cloud services evaluation. Although the concept Boosting Metrics was refined based on our work in the Cloud Computing domain, we believe it can be easily adapted to the evaluation work of other computing paradigms., Comment: Proceedings of the 27th IEEE International Conference on Advanced Information Networking and Applications (AINA 2013), pp. 381-388, Barcelona, Spain, March 25-28, 2013

Background: Spot pricing is considered as a significant supplement for building a full-fledged market economy for the Cloud ecosystem. However, it seems that both providers and consumers are still hesitating to enter the Cloud spot market. The relevant academic community also has conflicting opinions about Cloud spot pricing in terms of revenue generation. Aim: This work aims to systematically identify, assess, synthesize and report the published evidence in favor of or against spot-price scheme compared with fixed-price scheme of Cloud computing, so as to help relieve the aforementioned conflict. Method: We employed the systematic literature review (SLR) method to collect and investigate the empirical studies of Cloud spot pricing indexed by major electronic libraries. Results: This SLR identified 61 primary studies that either delivered discussions or conducted experiments to perform comparison between spot pricing and fixed pricing in the Cloud domain. The reported benefits and limitations were summarized to facilitate cost-benefit analysis of being a Cloud spot pricing player, while four types of theories were distinguished to help both researchers and practitioners better understand the Cloud spot market. Conclusions: This SLR shows that the academic community strongly advocates the emerging Cloud spot market. Although there is still a lack of practical and easily deployable market-driven mechanisms, the overall findings of our work indicate that spot pricing plays a promising role in the sustainability of Cloud resource exploitation.

We theoretically analyze contributions from the Kondo effect to the spin polarization and spin diffusion length in all-metal nonlocal spin valves. Interdiffusion of ferromagnetic atoms into the normal metal layer creates a region in which Kondo physics plays a significant role, giving discrepancies between experiment and existing theory. We start from a simple model and construct a modified spin drift-diffusion equation which clearly demonstrates how the Kondo physics not only suppresses the electrical conductivity but even more strongly reduces the spin diffusion length. We also present an explicit expression for the suppression of spin polarization due to Kondo physics in an illustrative regime. We compare this theory to previous experimental data to extract an estimate of the Elliot-Yafet probability for Kondo spin flip scattering of 0.7 $\pm$ 0.4, in good agreement with the value of 2/3 derived in the original theory of Kondo., Comment: 15 pages, 4 figures

[Background:] Software effort prediction methods and models typically assume positive correlation between software product complexity and development effort. However, conflicting observations, i.e. negative correlation between product complexity and actual effort, have been witnessed from our experience with the COCOMO81 dataset. [Aim:] Given our doubt about whether the observed phenomenon is a coincidence, this study tries to investigate if an increase in product complexity can result in the abovementioned counter-intuitive trend in software development projects. [Method:] A modified association rule mining approach is applied to the transformed COCOMO81 dataset. To reduce noise of analysis, this approach uses a constant antecedent (Complexity increases while Effort decreases) to mine potential consequents with pruning. [Results:] The experiment has respectively mined four, five, and seven association rules from the general, embedded, and organic projects data. The consequents of the mined rules suggested two main aspects, namely human capability and product scale, to be particularly concerned in this study. [Conclusions:] The negative correlation between complexity and effort is not a coincidence under particular conditions. In a software project, interactions between product complexity and other factors, such as Programmer Capability and Analyst Capability, can inevitably play a "friction" role in weakening the practical influences of product complexity on actual development effort.

We have observed the eigenmodes of coupled transverse domain walls in a pair of ferromagnetic nanowires. Although the pair is coupled magnetostatically, its spectrum is determined by a combination of pinning by edge roughness and dipolar coupling of the two walls. Because the corresponding energy scales are comparable, the coupling can be observed only at the smallest wire separations. A model of the coupled wall dynamics reproduces the experiment quantitatively, allowing for comparisons with the estimated pinning and domain wall coupling energies. The results have significant implications for the dynamics of devices based on coupled domain walls., Comment: 11 pages, 4 figures

Although Cloud computing emerged for business applications in industry, public Cloud services have been widely accepted and encouraged for scientific computing in academia. The recently available Google Compute Engine (GCE) is claimed to support high-performance and computationally intensive tasks, while little evaluation studies can be found to reveal GCE's scientific capabilities. Considering that fundamental performance benchmarking is the strategy of early-stage evaluation of new Cloud services, we followed the Cloud Evaluation Experiment Methodology (CEEM) to benchmark GCE and also compare it with Amazon EC2, to help understand the elementary capability of GCE for dealing with scientific problems. The experimental results and analyses show both potential advantages of, and possible threats to applying GCE to scientific computing. For example, compared to Amazon's EC2 service, GCE may better suit applications that require frequent disk operations, while it may not be ready yet for single VM-based parallel computing. Following the same evaluation methodology, different evaluators can replicate and/or supplement this fundamental evaluation of GCE. Based on the fundamental evaluation results, suitable GCE environments can be further established for case studies of solving real science problems., Comment: Proceedings of the 5th International Conference on Cloud Computing Technologies and Science (CloudCom 2013), pp. 1-8, Bristol, UK, December 2-5, 2013

Inadequate service availability is the top concern when employing Cloud computing. It has been recognized that zero downtime is impossible for large-scale Internet services. By learning from the previous and others' mistakes, nevertheless, it is possible for Cloud vendors to minimize the risk of future downtime or at least keep the downtime short. To facilitate summarizing lessons for Cloud providers, we performed a systematic survey of public Cloud service outage events. This paper reports the result of this survey. In addition to a set of findings, our work generated a lessons framework by classifying the outage root causes. The framework can in turn be used to arrange outage lessons for reference by Cloud providers. By including potentially new root causes, this lessons framework will be smoothly expanded in our future work., Comment: 11 pages

Commercial Cloud services have been increasingly supplied to customers in industry. To facilitate customers' decision makings like cost-benefit analysis or Cloud provider selection, evaluation of those Cloud services are becoming more and more crucial. However, compared with evaluation of traditional computing systems, more challenges will inevitably appear when evaluating rapidly-changing and user-uncontrollable commercial Cloud services. This paper proposes an expert system for Cloud evaluation that addresses emerging evaluation challenges in the context of Cloud Computing. Based on the knowledge and data accumulated by exploring the existing evaluation work, this expert system has been conceptually validated to be able to give suggestions and guidelines for implementing new evaluation experiments. As such, users can conveniently obtain evaluation experiences by using this expert system, which is essentially able to make existing efforts in Cloud services evaluation reusable and sustainable., Comment: 8 page, Proceedings of the 2012 International Conference on Cloud and Service Computing (CSC 2012), pp. 168-175, Shanghai, China, November 22-24, 2012

Within the service-oriented computing domain, Web service composition is an effective realization to satisfy the rapidly changing requirements of business. Therefore, the research into Web service composition has unfolded broadly. Since examining all of the related work in this area becomes a mission next to impossible, the classification of composition approaches can be used to facilitate multiple research tasks. However, the current attempts to classify Web service composition do not have clear objectives. Furthermore, the contexts and technologies of composition approaches are confused in the existing classifications. This paper proposes an effort-oriented classification matrix for Web service composition, which distinguishes between the context and technology dimension. The context dimension is aimed at analyzing the environment influence on the effort of Web service composition, while the technology dimension focuses on the technique influence on the effort. Consequently, besides the traditional classification benefits, this matrix can be used to build the basis of cost estimation for Web service composition in future research., Comment: 6 pages, Proceedings of the 5th International Conference on Internet and Web Applications and Services (ICIW 2010), pp. 357-362, Barcelona, Spain, May 9-15, 2010

Given the diversity of commercial Cloud services, performance evaluations of candidate services would be crucial and beneficial for both service customers (e.g. cost-benefit analysis) and providers (e.g. direction of service improvement). Before an evaluation implementation, the selection of suitable factors (also called parameters or variables) plays a prerequisite role in designing evaluation experiments. However, there seems a lack of systematic approaches to factor selection for Cloud services performance evaluation. In other words, evaluators randomly and intuitively concerned experimental factors in most of the existing evaluation studies. Based on our previous taxonomy and modeling work, this paper proposes a factor framework for experimental design for performance evaluation of commercial Cloud services. This framework capsules the state-of-the-practice of performance evaluation factors that people currently take into account in the Cloud Computing domain, and in turn can help facilitate designing new experiments for evaluating Cloud services., Comment: 8 pages, Proceedings of the 4th International Conference on Cloud Computing Technology and Science (CloudCom 2012), pp. 169-176, Taipei, Taiwan, December 03-06, 2012

Benefiting from the technology based strategies, Service-Oriented Architecture (SOA) has been able to achieve the general goals such as agility, flexibility, reusability and efficiency. Nevertheless, technical conditions alone cannot guarantee successful SOA implementations. As a valuable and necessary supplement, the space of technology independent strategies should also be explored. Through treating SOA system as an instance of organization and identifying the common ground on the similar process of SOA implementation and organization design, this paper uses existing work in organization theory area to inspire the research into technology independent strategies of SOA implementation. As a result, four preliminary strategies that can be applied to organizational area we identify to support SOA implementations. Furthermore, the novel methodology of investigating technology independent strategies for implementing SOA is revealed, which encourages interdisciplinary research across service-oriented computing and organization theory., Comment: 12 pages, Proceedings of the 6th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2011), pp. 143-154, Beijing, China, June 08-11, 2011

Expert judgment for software effort estimation is oriented toward direct evidences that refer to actual effort of similar projects or activities through experts' experiences. However, the availability of direct evidences implies the requirement of suitable experts together with past data. The circumstantial-evidence-based judgment proposed in this paper focuses on the development experiences deposited in human knowledge, and can then be used to qualitatively estimate implementation effort of different proposals of a new project by rational inference. To demonstrate the process of circumstantial-evidence-based judgment, this paper adopts propositional learning theory based diagnostic reasoning to infer and compare different effort estimates when implementing a Web service composition project with some different techniques and contexts. The exemplar shows our proposed work can help determine effort tradeoff before project implementation. Overall, circumstantial-evidence-based judgment is not an alternative but complementary to expert judgment so as to facilitate and improve software effort estimation., Comment: 10 pages, Proceedings of the 1st International Workshop on Evidential Assessment of Software Technologies (EAST 2011), pp. 18-27, Beijing, China, June 08-11, 2011

Given the continually increasing amount of commercial Cloud services in the market, evaluation of different services plays a significant role in cost-benefit analysis or decision making for choosing Cloud Computing. In particular, employing suitable metrics is essential in evaluation implementations. However, to the best of our knowledge, there is not any systematic discussion about metrics for evaluating Cloud services. By using the method of Systematic Literature Review (SLR), we have collected the de facto metrics adopted in the existing Cloud services evaluation work. The collected metrics were arranged following different Cloud service features to be evaluated, which essentially constructed an evaluation metrics catalogue, as shown in this paper. This metrics catalogue can be used to facilitate the future practice and research in the area of Cloud services evaluation. Moreover, considering metrics selection is a prerequisite of benchmark selection in evaluation implementations, this work also supplements the existing research in benchmarking the commercial Cloud services., Comment: 10 pages, Proceedings of the 13th ACM/IEEE International Conference on Grid Computing (Grid 2012), pp. 164-173, Beijing, China, September 20-23, 2012

Cloud Computing, as one of the most promising computing paradigms, has become increasingly accepted in industry. Numerous commercial providers have started to supply public Cloud services, and corresponding performance evaluation is then inevitably required for Cloud provider selection or cost-benefit analysis. Unfortunately, inaccurate and confusing evaluation implementations can be often seen in the context of commercial Cloud Computing, which could severely interfere and spoil evaluation-related comprehension and communication. This paper introduces a taxonomy to help profile and standardize the details of performance evaluation of commercial Cloud services. Through a systematic literature review, we constructed the taxonomy along two dimensions by arranging the atomic elements of Cloud-related performance evaluation. As such, this proposed taxonomy can be employed both to analyze existing evaluation practices through decomposition into elements and to design new experiments through composing elements for evaluating performance of commercial Cloud services. Moreover, through smooth expansion, we can continually adapt this taxonomy to the more general area of evaluation of Cloud Computing., Comment: 8 pages, Proceedings of the 5th International Conference on Cloud Computing (IEEE CLOUD 2012), pp. 344-351, Honolulu, Hawaii, USA, June 24-29, 2012

The magnetostatic interaction between two oppositely charged transverse domain walls (DWs)in adjacent Permalloy nanowires is experimentally demonstrated. The dependence of the pinning strength on wire separation is investigated for distances between 13 and 125 nm, and depinning fields up to 93 Oe are measured. The results can be described fully by considering the interaction between the full complex distribution of magnetic charge within rigid, isolated DWs. This suggests the DW internal structure is not appreciably disturbed by the pinning potential, and that they remain rigid although the pinning strength is significant. This work demonstrates the possibility of non-contact DW trapping without DW perturbation and full continuous flexibility of the pinning potential type and strength. The consequence of the interaction on DW based data storage schemes is evaluated., Comment: 4 pages, 4 figures, 1 page supplimentary material (supporting.ps)