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This paper explores a novel method for enhancing binary classification models that assess code comment quality, leveraging Generative Artificial Intelligence to elevate model performance. By integrating 1,437 newly generated code-comment pairs, labeled as "Useful" or "Not Useful" and sourced from various GitHub repositories, into an existing C-language dataset of 9,048 pairs, we demonstrate substantial model improvements. Using an advanced Large Language Model, our approach yields a 5.78% precision increase in the Support Vector Machine (SVM) model, improving from 0.79 to 0.8478, and a 2.17% recall boost in the Artificial Neural Network (ANN) model, rising from 0.731 to 0.7527. These results underscore Generative AI's value in advancing code comment classification models, offering significant potential for enhanced accuracy in software development and quality control. This study provides a promising outlook on the integration of generative techniques for refining machine learning models in practical software engineering settings., Comment: Code Comment Quality Classification, Generative Artificial Intelligence, Support Vector Machines, Artificial Neural Networks, Natural Language Processing

The problems of quantum state preparation and matrix block-encoding are ubiquitous in quantum computing: they are crucial parts of various quantum algorithms for the purpose for initial state preparation as well as loading problem relevant data. We first present an algorithm based on QRS that prepares a quantum state $|\psi_f\rangle \propto \sum^N_{x=1} f(x)|x\rangle$. When combined with efficient reference states the algorithm reduces the cost of quantum state preparation substantially, if certain criteria on $f$ are met. When the preparation of the reference state is not the dominant cost, and the function $f$ and relevant properties are efficiently computable or provided otherwise with cost $o(N)$, the QRS-based method outperforms the generic state preparation algorithm, which has cost $O(N)$. We demonstrate the detailed performance (in terms of the number of Toffoli gates) of the QRS-based algorithm for quantum states commonly appearing in quantum applications, e.g., those with coefficients that obey power law decay, Gaussian, and hyperbolic tangent, and compare it with other methods. Then, we adapt QRS techniques to the matrix block-encoding problem and introduce a QRS-based algorithm for block-encoding a given matrix $A = \sum_{ij} A_{ij} |i\rangle \langle j|$. We work out rescaling factors for different access models, which encode how the information about the matrix is provided to the quantum computer. We exemplify these results for a particular Toeplitz matrix with elements $A_{{\mathbf{ij}}}= 1/\|{\mathbf{i}}-{\mathbf{j}}\|^2$, which appears in quantum chemistry, and PDE applications, e.g., when the Coulomb interaction is involved. Our work unifies, and in certain ways goes beyond, various quantum state preparation and matrix block-encoding methods in the literature, and gives detailed performance analysis of important examples that appear in quantum applications., Comment: 58 pages, 28 figures, 5 tables

We introduce and study a mathematical model of an art collector. In our model, the collector is a rational agent whose actions in the art market are driven by two competing long-term objectives, namely sustainable financial health and maintaining the collection. Mathematically, our model is a two-dimensional random linear dynamical system with transformation matrix of a peculiar type. In some examples we are able to show that within the Kelly-type optimization paradigm, that is optimizing the system's Lyapunov exponent over a set of policy parameters, the dilemma ``art or money" can be successfully resolved, namely the optimal policy creates a coexistence equilibrium where the value of both is increasing over the time.

Exploring operational regimes of many-body cavity QED with multi-level atoms remains an exciting research frontier for their enhanced storage capabilities of intra-level quantum correlations. In this work, we consider an experimentally feasible many-body cavity QED model describing a four-level system, where each of those levels is formed from a combination of different spin and momentum states of ultra-cold atoms in a cavity. The resulting model comprises a pair of Dicke Hamiltonians constructed from pseudo-spin operators, effectively capturing two intertwined superradiant phase transitions. The phase diagram reveals regions featuring weak and strong entangled states of spin and momentum atomic degrees of freedom. These states exhibit different dynamical responses, ranging from slow to fast relaxation, with the added option of persistent entanglement temporal oscillations. We discuss the role of cavity losses in steering the system's dynamics into such entangled states and propose a readout scheme that leverages different light polarizations within the cavity. Our work paves the way to connect the rich variety of non-equilibrium phase transitions that occur in many-body cavity QED to the buildup of quantum correlations in systems with multi-level atom descriptions., Comment: 13+12 pages, 8+2 figures

This paper presents a novel approach to enhance the performance of binary code comment quality classification models through the application of Generative Artificial Intelligence (AI). By leveraging the OpenAI API, a dataset comprising 1239 newly generated code-comment pairs, extracted from various GitHub repositories and open-source projects, has been labelled as "Useful" or "Not Useful", and integrated into the existing corpus of 9048 pairs in the C programming language. Employing a cutting-edge Large Language Model Architecture, the generated dataset demonstrates notable improvements in model accuracy. Specifically, when incorporated into the Support Vector Machine (SVM) model, a 6% increase in precision is observed, rising from 0.79 to 0.85. Additionally, the Artificial Neural Network (ANN) model exhibits a 1.5% increase in recall, climbing from 0.731 to 0.746. This paper sheds light on the potential of Generative AI in augmenting code comment quality classification models. The results affirm the effectiveness of this methodology, indicating its applicability in broader contexts within software development and quality assurance domains. The findings underscore the significance of integrating generative techniques to advance the accuracy and efficacy of machine learning models in practical software engineering scenarios., Comment: FIRE Track: Information Retrieval in Software Engineering (IRSE), 9 pages

The Boltzmann equation is a powerful theoretical tool for modeling the collective dynamics of quantum many-body systems subject to external perturbations. Analysis of the equation gives access to linear response properties including collective modes and transport coefficients, but often proves intractable due to computational costs associated with multidimensional integrals describing collision processes. Here, we present a method to resolve this bottleneck, enabling the study of a broad class of many-body systems that appear in fundamental science contexts and technological applications. Specifically, we demonstrate that a Gaussian mixture model can accurately represent equilibrium distribution functions, thereby allowing efficient evaluation of collision integrals. Inspired by cold atom experiments, we apply this method to investigate the collective behavior of a quantum Bose-Fermi mixture of cold atoms in a cigar-shaped trap, a system that is particularly challenging to analyze. We focus on monopole and quadrupole collective modes above the Bose-Einstein transition temperature, and find a rich phenomenology that spans interference effects between bosonic and fermionic collective modes, dampening of these modes, and the emergence of hydrodynamics in various parameter regimes. These effects are readily verifiable experimentally., Comment: 32 page (19 pages of the main text), 10 figures (7 are in the main text)

Interacting mixtures of bosons and fermions are ubiquitous in nature. They form the backbone of the standard model of physics, provide a framework for understanding quantum materials and are of technological importance in helium dilution refrigerators. However, the description of their coupled thermodynamics and collective behaviour is challenging. Bose-Fermi mixtures of ultracold atoms provide a platform to investigate their properties in a highly controllable environment, where the species concentration and interaction strength can be tuned at will. Here we characterize the collective oscillations of spin-polarized fermionic impurities immersed in a Bose-Einstein condensate as a function of the interaction strength and temperature. For strong interactions, the Fermi gas perfectly mimics the superfluid hydrodynamic modes of the condensate, from low-energy quadrupole modes to high-order Faraday excitations. With an increasing number of bosonic thermal excitations, the dynamics of the impurities cross over from the collisionless to the hydrodynamic regime, reminiscent of the emergence of hydrodynamics in two-dimensional electron fluids., Comment: Published version

We introduce a framework for fault-tolerant post-selection (FTPS) of fault-tolerant codes and channels -- such as those based on surface-codes -- using soft-information metrics based on visible syndrome and erasure information. We introduce several metrics for ranking configurations of syndromes and erasures. In particular, we introduce the \emph{logical gap} (and variants thereof) as a powerful soft-information metric for predicting logical error rates of fault-tolerant channels based on topological error-correcting codes. The logical gap is roughly the unsigned weight difference between inequivalent logical corrections and is adaptable to any tailored noise model or decoder. We deploy this framework to prepare high-quality surface code magic states with low overhead under a model of independent and identically distributed (\emph{i.i.d.}) Pauli and erasure errors. Post-selection strategies based on the logical gap can suppress the encoding error rate of a magic state preparation channel to the level of the physical error rate with low overhead. For example, when operating at $60\%$ the bulk threshold of the corresponding surface code, an overall reduction of the encoding error rate by a factor of $15$ is achievable with a relative overhead factor of ${< 2}$ (approximately $23$ times less than that of simple syndrome-counting rules). We analyze a schematic buffer architecture for implementing post-selection rules on magic state factories in the context of magic state distillation. The FTPS framework can be utilized for mitigating errors in more general fault-tolerant logical channels., Comment: 10+7 pages, 13 figures, comments welcome

Demand for energy has increased significantly across the globe due to increase in population and economic growth. Growth in energy demand poses serious threat to the environment since majority of the energy sources are non-renewable and based on fossil fuels, which leads to emission of harmful greenhouse gases. Organizations across the world are facing challenges in transitioning from fossil fuels-based sources to greener sources to reduce their carbon footprint. As a step towards achieving Net-Zero emission target, we present a scalable AI based solution that can be used by organizations to increase their overall renewable electricity share in total energy consumption. Our solution provides facilities with accurate energy demand forecast, recommendation for procurement of renewable electricity to optimize cost and carbon offset recommendations to compensate for Greenhouse Gas (GHG) emissions. This solution has been used in production for more than a year for four facilities and has increased their renewable electricity share significantly., Comment: 8 pages, 10 Figures, 3 tables, 20 References, IEEE Conference template

The utility of near-term quantum computers and simulators is likely to rely upon software-hardware co-design, with error-aware algorithms and protocols optimized for the platforms they are run on. Here, we show how knowledge of noise in a system can be exploited to improve the design of gate-based quantum simulation algorithms. We concretely demonstrate this co-design in the context of a trapped ion quantum simulation of the dynamics of a Heisenberg spin model. Specifically, we derive a theoretical noise model describing unitary gate errors due to heating of the ions' collective motion, finding that the temporal correlations in the noise induce an optimal gate depth. We then illustrate how tailored feedforward control can be used to mitigate unitary gate errors and improve the simulation outcome. Our results provide a practical guide to the co-design of gate-based quantum simulation algorithms., Comment: 12 pages, 8 figures

We study the spatio-temporal spreading of correlations in an ensemble of spins due to dissipation characterized by short- and long-range spatial profiles. We consider systems initially in an uncorrelated state, and find that correlations widen and contract in a novel pattern intimately related to both the dissipative nature of the dynamical channel and its spatial profile. Additionally, we make a methodological contribution by generalizing non-equilibrium spin-wave theory to the case of dissipative systems and derive equations of motion for any translationally invariant spin chain whose dynamics can be described by a combination of Hamiltonian interactions and dissipative Lindblad channels. Our work aims at extending the study of correlation dynamics to purely dissipative quantum simulators and compare them with the established paradigm of correlations spreading in hamiltonian systems., Comment: 10 pages, 2 figures, builds on topic introduced in arXiv:2101.06445v2

Computational simulations of nuclear magnetic resonance (NMR) experiments are essential for extracting information about molecular structure and dynamics, but are often intractable on classical computers for large molecules such as proteins and protocols such as zero-field NMR. We demonstrate the first quantum simulation of a NMR spectrum, computing the zero-field spectrum of the methyl group of acetonitrile on a trapped-ion quantum computer. We reduce the sampling cost of the quantum simulation by an order of magnitude using compressed sensing techniques. Our work opens a new practical application for quantum computation, and we show how the inherent decoherence of NMR systems may enable the simulation of classically hard molecules on near-term quantum hardware., Comment: 5 pages + 3 figures (main text), 10 pages + 6 figures (supplementary material)

We investigate the behavior of a finite-momentum impurity immersed in a weakly interacting three-dimensional Bose-Einstein condensate (BEC) of ultra-cold atoms, giving a detailed account of the dynamical quantum Cherenkov transition discussed in Ref. [arXiv:2101.00030]. Using a time-dependent variational approach, we identify a transition in the far-from-equilibrium dynamics of the system after the attractive short-range impurity-boson interaction is quenched on. The transition occurs as the impurity's velocity crosses an interaction-dependent critical value, and manifests in the long-time behavior of the Loschmidt echo and average impurity velocity. This behavior is also reflected in the finite momentum ground state of the system, where the group velocity of the interaction-dressed impurity loses it's dependence on the total momentum of the system as the critical point is crossed. The transition we discuss should be experimentally observable via a variety of common protocols in ultracold atomic systems such as time-of-flight imaging, RF spectroscopy, Ramsey interferometry, and absorption imaging., Comment: 15 pages, 7 figures

Controlling the spread of correlations in quantum many-body systems is a key challenge at the heart of quantum science and technology. Correlations are usually destroyed by dissipation arising from coupling between a system and its environment. Here, we show that dissipation can instead be used to engineer a wide variety of spatio-temporal correlation profiles in an easily tunable manner. We describe how dissipation with any translationally-invariant spatial profile can be realized in cold atoms trapped in an optical cavity. A uniform external field and the choice of spatial profile can be used to design when and how dissipation creates or destroys correlations. We demonstrate this control by preferentially generating entanglement at a desired wavevector. We thus establish non-local dissipation as a new route towards engineering the far-from-equilibrium dynamics of quantum information, with potential applications in quantum metrology, state preparation, and transport., Comment: 6+10 pages, 4+2 figures

The challenge of understanding the dynamics of a mobile impurity in an interacting quantum many-body medium comes from the necessity of including entanglement between the impurity and excited states of the environment in a wide range of energy scales. In this paper, we investigate the motion of a finite mass impurity injected into a three-dimensional quantum Bose fluid as it starts shedding Bogoliubov excitations. We uncover a transition in the dynamics as the impurity's velocity crosses a critical value which depends on the strength of the interaction between the impurity and bosons as well as the impurity's recoil energy. We find that in injection experiments, the two regimes differ not only in the character of the impurity velocity abatement, but also exhibit qualitative differences in the Loschmidt echo, density ripples excited in the BEC, and momentum distribution of scattered bosonic particles. The transition is a manifestation of a dynamical quantum Cherenkov effect, and should be experimentally observable with ultracold atoms using Ramsey interferometry, RF spectroscopy, absorption imaging, and time-of-flight imaging., Comment: 5 pages, 3 figures + 4 pages, 3 figures

In this paper, we collect and study Twitter communications to understand the societal impact of COVID-19 in the United States during the early days of the pandemic. With infections soaring rapidly, users took to Twitter asking people to self isolate and quarantine themselves. Users also demanded closure of schools, bars, and restaurants as well as lockdown of cities and states. We methodically collect tweets by identifying and tracking trending COVID-related hashtags. We first manually group the hashtags into six main categories, namely, 1) General COVID, 2) Quarantine, 3) Panic Buying, 4) School Closures, 5) Lockdowns, and 6) Frustration and Hope}, and study the temporal evolution of tweets in these hashtags. We conduct a linguistic analysis of words common to all hashtag groups and specific to each hashtag group and identify the chief concerns of people as the pandemic gripped the nation (e.g., exploring bidets as an alternative to toilet paper). We conduct sentiment analysis and our investigation reveals that people reacted positively to school closures and negatively to the lack of availability of essential goods due to panic buying. We adopt a state-of-the-art semantic role labeling approach to identify the action words and then leverage a LSTM-based dependency parsing model to analyze the context of action words (e.g., verb deal is accompanied by nouns such as anxiety, stress, and crisis). Finally, we develop a scalable seeded topic modeling approach to automatically categorize and isolate tweets into hashtag groups and experimentally validate that our topic model provides a grouping similar to our manual grouping. Our study presents a systematic way to construct an aggregated picture of peoples' response to the pandemic and lays the groundwork for future fine-grained linguistic and behavioral analysis., Comment: Accepted for publication in IEEE SocialCom 2020. arXiv admin note: substantial text overlap with arXiv:2004.05451

In this paper, our goal is to analyze and compare cellular network usage data from pre-lockdown, during lockdown, and post-lockdown phases surrounding the COVID-19 pandemic to understand and model human mobility patterns during the pandemic, and evaluate the effect of lockdowns on mobility. To this end, we collaborate with one of the main cellular network providers in Brazil, and collect and analyze cellular network connections from 1400 antennas for all users in the city of Rio de Janeiro and its suburbs from March 1, 2020 to July 1, 2020. Our analysis reveals that the total number of cellular connections decreases to 78% during the lockdown phase and then increases to 85% of the pre-COVID era as the lockdown eases. We observe that as more people work remotely, there is a shift in the antennas incurring top 10% of the total traffic, with the number of connections made to antennas in downtown Rio reducing drastically and antennas at other locations taking their place. We also observe that while nearly 40-45% users connected to only 1 antenna each day during the lockdown phase indicating no mobility, there are around 4% users (i.e., 80K users) who connected to more than 10 antennas, indicating very high mobility. Finally, we design an interactive tool that showcases mobility patterns in different granularities that can potentially help people and government officials understand the mobility of individuals and the number of COVID cases in a particular neighborhood. Our analysis, inferences, and interactive showcasing of mobility patterns based on large-scale data can be extrapolated to other cities of the world and has the potential to help in designing more effective pandemic management measures in the future., Comment: 12 pages

The self-similar momentum ordinary differential equation (MODE) and the self-similar partial differential equation (MPDE) have been derived and the investigation of the integrability of the MODE and the MPDE has been done by performing Painlev\'e test. A detailed discussion of the leading order behavior of the MODE and the MPDE has been presented with the latter being analyzed for the cases in which terms of increasing orders of Reynolds number have been considered. We have provided a brief introduction to Lie point symmetries and have found the Lie infinitesimal operator which when acts on the MPDE to order $\mathcal{O}(R)$ satisfies the Lie symmetry condition. Explicit calculations and expressions for the Lie prolongation terms have been presented. We have also investigated the integrability of various self-similar equations that arise from the generalized self-similar equation for different values of constants $\alpha_{1,2,3}$. Foundational work on transitional boundary solutions has been presented and transition solutions have been found via application of a junction condition at the leading edge-trailing edge boundary domain. A detailed discussion of semi-analytical solutions via the homotopy perturbation method is presented. We find semi-analytical solutions to the Falkner-Skan equation and the MODE by considering a Taylor series expansion as the initial approximation. An algorithmic scheme that involves consideration of a multi-dimensional Taylor expansion as the initial approximation to the MPDE has been presented., Comment: 45 pages, 1 figure, 7 tables. arXiv admin note: text overlap with arXiv:1910.03502

In-network caching is likely to become an integral part of various networked systems (e.g., 5G networks, LPWAN and IoT systems) in the near future. In this paper, we compare and contrast model-based and machine learning approaches for designing caching and routing strategies to improve cache network performance (e.g., delay, hit rate). We first outline the key principles used in the design of model-based strategies and discuss the analytical results and bounds obtained for these approaches. By conducting experiments on real-world traces and networks, we identify the interplay between content popularity skewness and request stream correlation as an important factor affecting cache performance. With respect to routing, we show that the main factors impacting performance are alternate path routing and content search. We then discuss the applicability of multiple machine learning models, specifically reinforcement learning, deep learning, transfer learning and probabilistic graphical models for the caching and routing problem.

In this paper, we collect and study Twitter communications to understand the socio-economic impact of COVID-19 in the United States during the early days of the pandemic. Our analysis reveals that COVID-19 gripped the nation during this time as is evidenced by the significant number of trending hashtags. With infections soaring rapidly, users took to Twitter asking people to self isolate and quarantine themselves. Users also demanded closure of schools, bars, and restaurants as well as lockdown of cities and states. The communications reveal the ensuing panic buying and the unavailability of some essential goods, in particular toilet paper. We also observe users express their frustration in their communications as the virus spread continued. We methodically collect a total of 530,206 tweets by identifying and tracking trending COVID-related hashtags. We then group the hashtags into six main categories, namely 1) General COVID, 2) Quarantine, 3) Panic Buying, 4) School Closures, 5) Lockdowns, and 6) Frustration and Hope, and study the temporal evolution of tweets in these hashtags. We conduct a linguistic analysis of words common to all the hashtag groups and specific to each hashtag group. Our preliminary study presents a succinct and aggregated picture of people's response to the pandemic and lays the groundwork for future fine-grained linguistic and behavioral analysis.

In the context of the ongoing Covid-19 pandemic, several reports and studies have attempted to model and predict the spread of the disease. There is also intense debate about policies for limiting the damage, both to health and to the economy. On the one hand, the health and safety of the population is the principal consideration for most countries. On the other hand, we cannot ignore the potential for long-term economic damage caused by strict nation-wide lockdowns. In this working paper, we present a quantitative way to compute lockdown decisions for individual cities or regions, while balancing health and economic considerations. Furthermore, these policies are learnt automatically by the proposed algorithm, as a function of disease parameters (infectiousness, gestation period, duration of symptoms, probability of death) and population characteristics (density, movement propensity). We account for realistic considerations such as imperfect lockdowns, and show that the policy obtained using reinforcement learning is a viable quantitative approach towards lockdowns.

We provide an overview of the leading edge problem in this paper. We have used a self-similar function having a dependence on both the self-similar variable $\eta$ and Reynold's number R to covert the momentum and energy equations into a fourth-order, non-linear partial differential equation (PDE) and a second-order, non-linear PDE respectively. Attempts have been made to solve the energy equation in a variety of ways, which include solving the PDE approximating the terms of the order $\mathcal{O}(R^{2})$ and solving the PDE via the method of characteristics, but mostly being able to solve the energy PDE sans solving the momentum PDE. The complexities involved in solving the momentum PDE have been discussed and plausible approximate solutions have been given. The importance of boundary conditions and how they influence the solution to the energy PDE has been discussed. We have also shown how the energy PDE can be defined as a well-posed hyperbolic initial-boundary value problem in the leading edge. We conclude the paper by showing an approximate solution to the heat transfer coefficient and plot its characteristic behavior., Comment: 14 pages, 1 figure. V2: minor changes and added co-author

Floquet engineering offers tantalizing opportunities for controlling the dynamics of quantum many body systems and realizing new nonequilibrium phases of matter. However, this approach faces a major challenge: generic interacting Floquet systems absorb energy from the drive, leading to uncontrolled heating which washes away the sought after behavior. How to achieve and control a non-trivial nonequilibrium steady state is therefore of crucial importance. In this work, we study the dynamics of an interacting one-dimensional periodically-driven electronic system coupled to a phonon heat bath. Using the Floquet-Boltzmann equation (FBE) we show that the electronic populations of the Floquet eigenstates can be controlled by the dissipation. We find the regime in which the steady state features an insulatorlike filling of the Floquet bands, with a low density of additional excitations. Furthermore, we develop a simple rate equation model for the steady state excitation density that captures the behavior obtained from the numerical solution of the FBE over a wide range of parameters., Comment: 6+6 pages, 4 figures

When a mobile impurity interacts with a surrounding bath of bosons, it forms a polaron. Numerous methods have been developed to calculate how the energy and the effective mass of the polaron are renormalized by the medium for equilibrium situations. Here we address the much less studied non-equilibrium regime and investigate how polarons form dynamically in time. To this end, we develop a time-dependent renormalization group approach which allows calculations of all dynamical properties of the system and takes into account the effects of quantum fluctuations in the polaron cloud. We apply this method to calculate trajectories of polarons following a sudden quench of the impurity-boson interaction strength, revealing how the polaronic cloud around the impurity forms in time. Such trajectories provide additional information about the polaron's properties which are challenging to extract directly from the spectral function measured experimentally using ultracold atoms. At strong couplings, our calculations predict the appearance of trajectories where the impurity wavers back at intermediate times as a result of quantum fluctuations. Our method is applicable to a broader class of non-equilibrium problems. We also apply it to calculate the spectral function and find good agreement with experimental results. At very strong couplings, we predict that quantum fluctuations lead to the appearance of a dark continuum with strongly suppressed spectral weight at low energies. While our calculations start from an effective Fr\"ohlich Hamiltonian describing impurities in a three-dimensional Bose-Einstein condensate, we also calculate the effects of additional terms in the Hamiltonian beyond the Fr\"ohlich paradigm. We demonstrate that the main effect of these additional terms on the attractive side of a Feshbach resonance is to renormalize the coupling strength of the effective Fr\"ohlich model., Comment: 19 pages, 7 figures, 2 appendices

Conventional wisdom suggests that the long time behavior of isolated interacting periodically driven (Floquet) systems is a featureless maximal entropy state characterized by an infinite temperature. Efforts to thwart this uninteresting fixed point include adding sufficient disorder to realize a Floquet many-body localized phase or working in a narrow region of drive frequencies to achieve glassy non-thermal behavior at long time. Here we show that in clean systems the Floquet eigenstates can exhibit non-thermal behavior due to finite system size. We consider a one-dimensional system of spinless fermions with nearest-neighbor interactions where the interaction term is driven. Interestingly, even with no static component of the interaction, the quasienergy spectrum contains gaps and a significant fraction of the Floquet eigenstates, at all quasienergies, have non-thermal average doublon densities. We show that this non-thermal behavior arises due to emergent integrability at large interaction strength and discuss how the integrability breaks down with power-law dependence on system size., Comment: 10+8 pages, 13 figures

External driving is emerging as a promising tool for exploring new phases in quantum systems. The intrinsically non-equilibrium states that result, however, are challenging to describe and control. We study the steady states of a periodically driven one-dimensional electronic system, including the effects of radiative recombination, electron-phonon interactions, and the coupling to an external fermionic reservoir. Using a kinetic equation for the populations of the Floquet eigenstates, we show that the steady-state distribution can be controlled using the momentum and energy relaxation pathways provided by the coupling to phonon and Fermi reservoirs. In order to utilize the latter, we propose to couple the system and reservoir via an energy filter which suppresses photon-assisted tunneling. Importantly, coupling to these reservoirs yields a steady state resembling a band insulator in the Floquet basis. The system exhibits incompressible behavior, while hosting a small density of excitations. We discuss transport signatures, and describe the regimes where insulating behavior is obtained. Our results give promise for realizing Floquet topological insulators., Comment: 24 pages, 7 figures; with appendices

We investigate the problem of optimal request routing and content caching in a heterogeneous network supporting in-network content caching with the goal of minimizing average content access delay. Here, content can either be accessed directly from a back-end server (where content resides permanently) or be obtained from one of multiple in-network caches. To access a piece of content, a user must decide whether to route its request to a cache or to the back-end server. Additionally, caches must decide which content to cache. We investigate the problem complexity of two problem formulations, where the direct path to the back-end server is modeled as i) a congestion-sensitive or ii) a congestion-insensitive path, reflecting whether or not the delay of the uncached path to the back-end server depends on the user request load, respectively. We show that the problem is NP-complete in both cases. We prove that under the congestion-insensitive model the problem can be solved optimally in polynomial time if each piece of content is requested by only one user, or when there are at most two caches in the network. We also identify a structural property of the user-cache graph that potentially makes the problem NP-complete. For the congestion-sensitive model, we prove that the problem remains NP-complete even if there is only one cache in the network and each content is requested by only one user. We show that approximate solutions can be found for both models within a (1-1/e) factor of the optimal solution, and demonstrate a greedy algorithm that is found to be within 1% of optimal for small problem sizes. Through trace-driven simulations we evaluate the performance of our greedy algorithms, which show up to a 50% reduction in average delay over solutions based on LRU content caching., Comment: Infocom

Hybrid networks consisting of MANET nodes and cellular infrastructure have been recently proposed to improve the performance of military networks. Prior work has demonstrated the benefits of in-network content caching in a wired, Internet context. We investigate the problem of developing optimal routing and caching policies in a hybrid network supporting in-network caching with the goal of minimizing overall content-access delay. Here, needed content may always be accessed at a back-end server via the cellular infrastructure; alternatively, content may also be accessed via cache-equipped "cluster" nodes within the MANET. To access content, MANET nodes must thus decide whether to route to in-MANET cluster nodes or to back-end servers via the cellular infrastructure; the in-MANET cluster nodes must additionally decide which content to cache. We model the cellular path as either i) a congestion-insensitive fixed-delay path or ii) a congestion-sensitive path modeled as an M/M/1 queue. We demonstrate that under the assumption of stationary, independent requests, it is optimal to adopt static caching (i.e., to keep a cache's content fixed over time) based on content popularity. We also show that it is optimal to route to in-MANET caches for content cached there, but to route requests for remaining content via the cellular infrastructure for the congestion-insensitive case and to split traffic between the in-MANET caches and cellular infrastructure for the congestion-sensitive case. We develop a simple distributed algorithm for the joint routing/caching problem and demonstrate its efficacy via simulation., Comment: submitted to Milcom 2014

Wireless sensor network (WSN) is a collection of nodes which can communicate with each other without any prior infrastructure along with the ability to collect data autonomously and effectively after being deployed in an ad-hoc fashion to monitor a given area. One major problem encountered in data gathering wireless systems is to obtain an optimal balance among the number of nodes deployed, energy efficiency and lifetime as energy of nodes cannot be replenished. In this paper we propose first a scheme to estimate the number of nodes to be deployed in a WSN for a predetermined lifetime so that total energy utilization and complete connectivity are ensured under all circumstances. This scheme also guarantees that during each data gathering cycle, every node dissipates the requisite amount of energy, which thus minimizes the number of nodes required to achieve the desired network lifetime. Second, this paper has proposed a framework to conduct data gathering in WSN. Extensive simulations have been carried out in ns2 to establish the effectiveness of this framework., Comment: Accepted in the International Congress for Global Science and Technology (ICGST) in the Journal of Computer Network and Internet Research (CNIR), 2010

Static analysis (aka offline analysis) of a model of an IP network is useful for understanding, debugging, and verifying packet flow properties of the network. There have been static analysis approaches proposed in the literature for networks based on model checking as well as graph reachability. Abstract interpretation is a method that has typically been applied to static analysis of programs. We propose a new, abstract-interpretation based approach for analysis of networks. We formalize our approach, mention its correctness guarantee, and demonstrate its flexibility in addressing multiple network-analysis problems that have been previously solved via tailor-made approaches. Finally, we investigate an application of our analysis to a novel problem -- inferring a high-level policy for the network -- which has been addressed in the past only in the restricted single-router setting., Comment: 8 pages

This report consolidates research carried out at Clemson University and Stanford University where a series of measurements were undertaken to identify the man-made radiation present in four bands used by rather different services, namely, L1 Band (1563.42 1587.42 MHz), the Unified S-Band (2025 2110 MHz), the 2.4 GHz Industrial, Scientific and Medical (ISM) Band (2400 2482.50 MHz), and the 23.6-24.0 GHz Passive Sensing Band. Results show that there were distinctive differences in the measurement data in the frequency bands, which should be expected based on the function/regulation associated with each. The GPS L1 Band had little to none terrestrial man-made sources, but the ISM 2.4 GHz Band had a large number of man-made sources regardless of the site and the time. The Unified S Band showed mixed results depending on the sites. The Passive Sensing Band does not contain appreciable man-made radiation.

Wind tunnel tests have been conducted on an NACA 2412 airfoil section at Reynolds number of 2.2 x 10(exp 6) and Mach number of 0.13. Detailed measurements of flow fields associated with turbulent boundary layers have been obtained at angles of attack of 12.4 degrees, 14.4 degrees, and 16.4 degrees. Pre- and post-separated velocity and pressure survey results over the airfoil and in the associated wake are presented. Extensive force, pressure, tuft survey, hot-film survey, local skin friction, and boundary layer data are also included. Pressure distributions and separation point locations show good agreement with theory for the two layer angles of attack. Boundary layer displacement thickness, momentum thickness, and shape factor agree well with theory up to the point of separation. There is considerable disparity between extent of flow reversal in the wake as measured by pressure and hot-film probes. The difference is attributed to the intermittent nature of the flow reversal.

Wind tunnel tests were conducted on the NASA LS(1)-0421 Mod, NACA 2412 and NASA GA(W)-2 airfoil sections at a Reynolds number of 2.2 x 10(6) and a Mach number of 0.13. Detailed measurements of flow fields associated with turbulent boundary layers of these airfoils were obtained at pre-stall, near-stall, and post-stall angles of attack. Velocity and pressure survey results over the airfoil and in the associated wake, are presented for fully attached flow conditions through the stalled flow condition. Extensive force, pressure, tuft survey, hot-film survey, local skin friction and boundary layer data are also included.

Results were given on experimental studies of flow separation and stalling on a two-dimensional GA(W)-1 17 percent thick airfoil with an extended Fowler flap. Experimental velocity profiles obtained from a five tube probe survey with optimum flap gap and overlap setting (flap at 40 deg) are shown at various stations above, below, and behind the airfoil/flap combination for various angles of attack. The typical zones of steady flow, intermittent turbulence, and large scale turbulence were obtained from a hot wire anemometer survey and are depicted graphically for an angle of attack of 12.5 deg. Local skin friction distributions were obtained and are given for various angles of attack. Computer plots of the boundary layer profiles are shown for the case of the flap at 40 deg. Static pressure contours are also given. A GA(W)-2 section model was fabricated with 30 percent Fowler flaps and with pressure tabs.

Detailed experimental measurements have been made of separated flow fields on a two-dimensional airfoil at low speeds. A rather small pitch yaw pressure probe was chosen. This probe has the capability of remote traversing in the vertical axis and remote yawing of plus or minus 180 deg. The calibration of the probe indicates a useful pitch angle range of about plus or minus 45 deg. The probe and its calibrations provide static and total pressure information as well as three components of velocity. Description and calibration of the probe and typical velocity and pressure plots of the separated flow fields are included.

Detailed measurements of flow fields associated with low-speed turbulent boundary layers were made for the 17% thick GA(W)-1 airfoil section at nominal angles of attack of 10 deg, 14 deg, and 18 deg, Reynolds number 2.2 x 10, and Mach number 0.13. The data include pressure and velocity surveys of the pre- and post-separated regions on the airfoil and the associated wake. The boundary layer characteristics including regions of separation on the airfoil are also presented.

Wind tunnel tests have been carried out to develop a spoiler lateral control system for use with the GA(W)-1 airfoil with a 30% Fowler flap. Tests show that unfavorable aerodynamic interactions can occur between spoiler and flap for large flap deflections. Providing venting of lower surface air through the spoiler opening substantially improves performance. Results of tests with a number of spoiler and cavity shapes are presented and discussed. Applications of two-dimensional wind tunnel results to the design of satisfactory manual lateral control systems are discussed.

A two-dimensional wind-tunnel evaluation of two Fowler flap configurations on the new GA(W)-1 airfoil was conducted. One configuration used a computer-designed 29-percent chord Fowler flap. The second configuration was modified to have increased Fowler action with a 30-percent chord flap. Force, pressure, and flow-visualization data were obtained at Reynolds numbers of 2.2 million to 2.9 million. Optimum slot geometry and performance were found to be close to computer predictions. A C sub L max of 3.8 was achieved. Optimum flap deflection, slot gap, and flap overlap are presented as functions of C sub L. Tests were made with the lower surface cusp filled in to show the performance penalties that result. Some data on the effects of adding vortex generators and hinged-plate spoilers were obtained.

Experimental studies of turbulent separation on airfoils have been conducted to aid in improving theoretical models of post-stall airfoil behavior. The studies utilize a variety of pressure and hot-film probes. The split-film anemometer has proved particularly valuable for measurement of highly turbulent reversing flows. Suggested techniques for on-line digital computer processing of the data are discussed.

Two dimensional airfoil testing was conducted at the Wichita State University Beech Wind Tunnel for a number of years. The instrumentation developed and adapted during this period of testing for determination of flow fields along with traversing mechanisms for these probes are discussed. In addition, some of the techniques used to account for interference effects associated with the apparatus used for this two dimensional testing are presented. The application of a minicomputer to the data reduction and presentation is discussed.

Wind tunnel tests have been conducted on a NASA GA(W)-2 airfoil section at Reynolds number of 2.2 x 10(exp 6) and Mach number of 0.13. Detailed measurements of flow fields associated with turbulent boundary layers have been obtained at angles of attack of 10.3, 14.4, and 18.3 deg. Pre- and post-separated velocity and pressure survey results over the airfoil and in the associated wake are presented. Extensive force, pressure, tuft survey, hot-film survey, local skin friction, and boundary layer data are also included. Pressure distributions and separation point locations show good agreement with theory for the two lower angles of attack. Boundary layer displacement thickness, momentum thickness, and shape factor agree well with theory up to the point of separation. There is considerable disparity between extent of flow reversal in the wake as measured by pressure and hot-film probes. The difference is attributed to the intermittent nature of the flow reversal.

Wind tunnel force and pressure tests were conducted for the GA(W)-1 airfoil equipped with a 20% aileron, and pressure tests were conducted with a 30% Fowler flap. All tests were conducted at a Reynolds number of 2.2 and a Mach number of 0.13. The aileron provides control effectiveness similar to ailerons applied to more conventional airfoils. Effects of aileron gaps from 0% to 2% chord were evaluated, as well as hinge moment characteristics. The aft camber of the GA(W)-1 section results in a substantial up-aileron moment, but the hinge moments associated with aileron deflection are similar to other configurations. Fowler flap pressure distributions indicate that unseparated flow is achieved for flap settings up to 40 deg., over a limited angle of attack range. Theoretical pressure distributions compare favorably with experiments for low flap deflections, but show substantial errors at large deflections.

Measurements of flow fields with low speed turbulent boundary layers were made for the GA(W)-1 airfoil with a 0.30 c Fowler flap deflected 40 deg at angles of attack of 2.7 deg, 7.7 deg, and 12.8 deg, at a Reynolds number of 2.2 million, and a Mach number of 0.13. Details of velocity and pressure fields associated with the airfoil flap combination are presented for cases of narrow, optimum and wide slot gaps. Extensive flow field turbulence surveys were also conducted employing hot-film anemometry. For the optimum gap setting, the boundaries of the regions of flow reversal within the wake were determined by this technique for two angles of attack. Local skin friction distributions for the basic airfoil and the airfoil with flap (optimum gap) were obtained using the razor blade technique.

Research has been conducted on the nature of airfoil behavior at pre- and post-separated angles of attack. Detailed wind tunnel studies have been made of boundary layer and wake fields for the GA(W)-1 airfoil, and the airfoil with a 0.3 chord Fowler flap. Experimental data are compared with theoretical predictions from a multi-element viscous flow computer program. Theoretical predictions are reasonably accurate for unseparated flows, but have serious errors when separation is present. Some recent techniques for modeling post-separated flow behavior are discussed in light of the present experiments.

A small combination pitch-yaw probe designed to facilitate measurement of post-separated flow fields on airfoils is described, along with its calibration. A five-tube probe is found 'ideally suited' to separated-flow measurements because of the pitch and yaw angle information provided in addition to static and total pressures. Wall proximity effects (in a low-speed tunnel) are described. Procedures for measurements in flows with small inclinations in pitch and yaw, for large flow angles, and for scanning flows with large inclinations are indicated.

Detailed measurements of flow fields associated with low-speed turbulent boundary layers have been made for the 17% thick GA(W)-1 airfoil section at nominal angles of attack of 10, 14, and 18 deg; Reynolds number 2.2 million; and Mach number 0.13. The data include extensive pressure and velocity surveys of the pre- and post-separated regions on the airfoil and the associated wake. Integrated boundary-layer characteristics, including regions of separation on the airfoil, are also presented. The results indicate steep gradients of displacement thickness, momentum thickness, shape factor, and the separation streamline from the point of separation to the trailing edge of the airfoil. The present tests reveal that the region of flow reversal terminates within a suprisingly short distance of less than 20% chord downstream from the trailing edge for the test range of angle of attack.