cssi/SciSciGPT-SciSciNet huggingface dataset:
Selective addressing of solid-state spins at the nanoscale via magnetic resonance frequency encoding

The nitrogen vacancy centre in diamond is a leading platform for nanoscale sensing and imaging, as well as quantum information processing in the solid state. To date, individual control of two nitrogen vacancy electronic spins at the nanoscale has been demonstrated. However, a key challenge is to scale up such control to arrays of nitrogen vacancy spins. Here, we apply nanoscale magnetic resonance frequency encoding to realize site-selective addressing and coherent control of a four-site array of nitrogen vacancy spins. Sites in the array are separated by 100 nm, with each site containing multiple nitrogen vacancies separated by ~15 nm. Microcoils fabricated on the diamond chip provide electrically tuneable magnetic field gradients ~0.1 G/nm. Tailored application of gradient fields and resonant microwaves allow site-selective nitrogen vacancy spin manipulation and sensing applications, including Rabi oscillations, imaging, and nuclear magnetic resonance spectroscopy with nanoscale resolution. Microcoil-based magnetic resonance of solid-state spins provides a practical platform for quantum-assisted sensing, quantum information processing, and the study of nanoscale spin networks. Arrays of spins in solids are a promising modality for a wide range of quantum science applications—from sensing to information processing. A team led by Ronald Walsworth at Harvard University adapted methods from magnetic resonance imaging (MRI) to realize site-selective addressing and coherent control of small arrays of optically active electronic spins in diamond known as nitrogen vacancy (NV) colour centres. Microcoils fabricated on the diamond chip provide electrically tunable magnetic field gradients that allow selective NV spin addressing with 30 nm resolution. The team experimentally demonstrated site-selective NV electron spin resonance spectroscopy, Rabi oscillations, Fourier magnetic imaging, and nuclear magnetic resonance (NMR) spectroscopy. The approach should be scalable to selective coherent control of large-scale arrays of strongly interacting NVs, with a broad spectrum of high-impact quantum science applications.
Slopey quantizers are locally optimal for Witsenhausen's counterexample

We study the perfect Bayesian equilibria of a leader-follower game of incomplete information. The follower makes a noisy observation of the leader's action (who moves first) and chooses an action minimizing her expected deviation from the leader's action. Knowing this, leader who observes the realization of the state, chooses an action that minimizes her distance to the state of the world and the ex-ante expected deviation from the follower's action. We show the existence of what we call “near piecewise-linear equilibria” when there is strong complementarity between the leader and the follower and the precision of the prior is poor. As a major consequence of this result, we prove local optimality of a class of slopey quantization strategies which had been suspected of being the optimal solution in the past, based on numerical evidence for Witsenhausen's counterexample.
Infinite Swapping using IID Samples

We propose a new method for estimating rare event probabilities when independent samples are available. It is assumed that the underlying probability measures satisfy a large deviation principle with a scaling parameter v that we call temperature. We show how by combining samples at different temperatures, one can construct an estimator with greatly reduced variance. Although as presented here the method is not as broadly applicable as other rare event simulation methods, such as splitting or importance sampling, it does not require any problem-dependent constructions.
A NOTE ON PRIMES IN SHORT INTERVALS

Montgomery and Soundararajan obtained evidence for the Gaussian distribution of primes in short intervals assuming a quantitative Hardy–Littlewood conjecture. In this article, we show that their methods may be modified and an average form of the Hardy–Littlewood conjecture suffices.
Simulating the Cosmic Dawn With Enzo

We review two decades of progress using the Enzo hydrodynamic cosmology code to simulate the Cosmic Dawn, a period of roughly 1 billion years beginning with the formation of the first stars in the universe, and ending with cosmic reionization. Using simulations of increasing size and complexity, working up in length and mass scale and to lower redshifts, a connected narrative is built up covering the entire epoch. In the first part of the paper, we draw on results we and our collaborators have achieved using the Enzo cosmological adaptive mesh refinement code. Topics include the formation of Population III stars, the transition to Population II star formation, chemical enrichment, the assembly of the first galaxies, their high redshift galaxy statistics, and their role in reionization. In the second part of the paper we highlight physical difficulties that will require new, more physically complex simulations to address, drawing from a broader literature survey. We discuss the healthy interplay between self-consistent numerical simulations and analytic and semi-analytic approaches. Finally, we discuss technical advances in hardware and software that will enable a new class of more realistic simulations to be carried out on exascale supercomputers in the future.
CHARACTERISTIC CLASSES FOR RIEMANNIAN FOLIATIONS

The purpose of this paper is to both survey and offer some new results on the non-triviality of the characteristic classes of Riemannian foliations. We give examples where the primary Pontrjagin classes are all linearly independent. The independence of the secondary classes is also discussed, along with their total variation. Finally, we give a negative solution of a conjecture that the map of classifying spaces FRΓq → FΓq is trivial for codimension q > 1.
Alternating Minimization Algorithm with Automatic Relevance Determination for Transmission Tomography under Poisson Noise

We propose a globally convergent alternating minimization (AM) algorithm for image reconstruction in transmission tomography, which extends automatic relevance determination (ARD) to Poisson noise models with Beer's law. The algorithm promotes solutions that are sparse in the pixel/voxel--difference domain by introducing additional latent variables, one for each pixel/voxel, and then learning these variables from the data using a hierarchical Bayesian model. Importantly, the proposed AM algorithm is free of any tuning parameters with image quality comparable to standard penalized likelihood methods. Our algorithm exploits optimization transfer principles which reduce the problem into parallel one-dimensional optimization tasks (one for each pixel/voxel), making the algorithm feasible for large-scale problems. This approach considerably reduces the computational bottleneck of ARD associated with the posterior variances. Positivity constraints inherent in transmission tomography problems are also enforced. ...
Exploring confinement in SU(N) gauge theories with double-trace Polyakov loop deformations

Recent results applying resurgence theory to finite-temperature field theories yield a detailed analytic structure determined by topological excitations. We examine finite-temperature SU(N) lattice gauge theories in light of these results. Double-trace Polyakov loop deformations move through different regions of the confined phase characterized by continuous change in the adjoint Polyakov loop. Lattice models show how the behavior of monopole constituents of calorons can change in the different confining regions. We conjecture that the pure SU(N) gauge theory is close to a special symmetric point where monopole effects give rise to Casimir string-tension scaling.
L2-NONEXPANSIVE NEURAL NETWORKS

A training method, system, and computer program product include training a neural network including at least one of using norm-pooling as a non-linear function, using a two-sided ReLU as a non-linear function, and increasing a confidence gap and further training such that the network comprises a non-expansive network.
Generalizing Informed Sampling for Asymptotically-Optimal Sampling-Based Kinodynamic Planning via Markov Chain Monte Carlo

Asymptotically-optimal motion planners such as RRT* have been shown to incrementally approximate the shortest path between start and goal states. Once an initial solution is found, their performance can be dramatically improved by restricting subsequent samples to regions of the state space that can potentially improve the current solution. When the motion-planning problem lies in a Euclidean space, this region X inf , called the informed set, can be sampled directly. However, when planning with differential constraints in non-Euclidean state spaces, no analytic solutions exists to sampling X inf directly. State-of-the-art approaches to sampling X inf in such domains such as Hierarchical Rejection Sampling (HRS) may still be slow in high -dimensional state space. This may cause the planning algorithm to spend most of its time trying to produces samples in X inf rather than explore it. In this paper, we suggest an alternative approach to produce samples in the informed set X inf for a wide range of settings. Our main insight is to recast this problem as one of sampling uniformly within the sub-level-set of an implicit non-convex function. This recasting enables us to apply Monte Carlo sampling methods, used very effectively in the Machine Learning and Optimization communities, to solve our problem. We show for a wide range of scenarios that using our sampler can accelerate the convergence rate to high-quality solutions in high-dimensional problems.
Fast Change Point Detection on Dynamic Social Networks

A number of real world problems in many domains (e.g. sociology, biology, political science and communication networks) can be modeled as dynamic networks with nodes representing entities of interest and edges representing interactions among the entities at different points in time. A common representation for such models is the snapshot model - where a network is defined at logical time-stamps. An important problem under this model is change point detection. In this work we devise an effective and efficient three-step-approach for detecting change points in dynamic networks under the snapshot model. Our algorithm achieves up to 9X speedup over the state-of-the-art while improving quality on both synthetic and real world networks.
Transformation properties for Dyson's rank function

At the 1987 Ramanujan Centenary meeting Dyson asked for a coherent group-theoretical structure for Ramanujan's mock theta functions analogous to Hecke's theory of modular forms. Many of Ramanujan's mock theta functions can be written in terms of $R(\zeta,q)$, where $R(z,q)$ is the two-variable generating function of Dyson's rank function and $\zeta$ is a root of unity. Building on earlier work of Watson, Zwegers, Gordon and McIntosh, and motivated by Dyson's question, Bringmann, Ono and Rhoades studied transformation properties of $R(\zeta,q)$. In this paper we strengthen and extend the results of Bringmann, Rhoades and Ono, and the later work of Ahlgren and Treneer. As an application we give a new proof of Dyson's rank conjecture and show that Ramanujan's Dyson rank identity modulo $5$ from the Lost Notebook has an analogue for all primes greater than $3$. The proof of this analogue was inspired by recent work of Jennings-Shaffer on overpartition rank differences mod $7$.
Embedding Lexical Features via Low-Rank Tensors

Modern NLP models rely heavily on engineered features, which often combine word and contextual information into complex lexical features. Such combination results in large numbers of features, which can lead to over-fitting. We present a new model that represents complex lexical features---comprised of parts for words, contextual information and labels---in a tensor that captures conjunction information among these parts. We apply low-rank tensor approximations to the corresponding parameter tensors to reduce the parameter space and improve prediction speed. Furthermore, we investigate two methods for handling features that include $n$-grams of mixed lengths. Our model achieves state-of-the-art results on tasks in relation extraction, PP-attachment, and preposition disambiguation.
LINK INVARIANTS FROM FINITE COXETER RACKS

We study Coxeter racks over ℤn and the knot and link invariants they define. We exploit the module structure of these racks to enhance the rack counting invariants and give examples showing that these enhanced invariants are stronger than the unenhanced rack counting invariants.
Glyph-aware Embedding of Chinese Characters

Given the advantage and recent success of English character-level and subword-unit models in several NLP tasks, we consider the equivalent modeling problem for Chinese. Chinese script is logographic and many Chinese logograms are composed of common substructures that provide semantic, phonetic and syntactic hints. In this work, we propose to explicitly incorporate the visual appearance of a character’s glyph in its representation, resulting in a novel glyph-aware embedding of Chinese characters. Being inspired by the success of convolutional neural networks in computer vision, we use them to incorporate the spatio-structural patterns of Chinese glyphs as rendered in raw pixels. In the context of two basic Chinese NLP tasks of language modeling and word segmentation, the model learns to represent each character’s task-relevant semantic and syntactic information in the character-level embedding.
Gradient descent GAN optimization is locally stable

Despite the growing prominence of generative adversarial networks (GANs), optimization in GANs is still a poorly understood topic. In this paper, we analyze the ``gradient descent'' form of GAN optimization, i.e., the natural setting where we simultaneously take small gradient steps in both generator and discriminator parameters. We show that even though GAN optimization does \emph{not} correspond to a convex-concave game (even for simple parameterizations), under proper conditions, equilibrium points of this optimization procedure are still \emph{locally asymptotically stable} for the traditional GAN formulation. On the other hand, we show that the recently proposed Wasserstein GAN can have non-convergent limit cycles near equilibrium. Motivated by this stability analysis, we propose an additional regularization term for gradient descent GAN updates, which \emph{is} able to guarantee local stability for both the WGAN and the traditional GAN, and also shows practical promise in speeding up convergence and addressing mode collapse.
Farthest point map on a centrally symmetric convex polyhedron

The farthest point map sends a point in a compact metric space to the set of points farthest from it. We focus on the case when this metric space is a convex centrally symmetric polyhedral surface, so that we can compose the farthest point map with the antipodal map. The purpose of this work is to study the properties of their composition. We show that: 1. the map has no generalized periodic points; 2. its limit set coincides with its generalized fixed point set; 3. each of its orbit converges; 4. its limit set is contained in a finite union of hyperbolas. We will define some of these terminologies later.
Quantum Algorithms for Simulated Annealing

This paper summarizes a quantum algorithm of [R.D. Somma, et.al., Phys. Rev. Lett. 101, 130504 (2008)] that simulates a classical annealing process for solving discrete optimization problems. The complexity of the quantum algorithm scales with the inverse square root of the spectral gap of an associated stochastic matrix. This represents a quadratic quantum speedup, in terms of the gap, with respect to classical simulated annealing.
Small representations of integers by integral quadratic forms

Abstract Given an isotropic quadratic form over a number field which assumes a value t, we investigate the distribution of points at which this value is assumed. Building on the previous work about the distribution of small-height zeros of quadratic forms, we produce bounds on height of points outside of some algebraic sets in a quadratic space at which the form assumes the value t. Our bounds on height are explicit in terms of the heights of the form, the space, the algebraic set and the value t.
MANA for MPI: MPI-Agnostic Network-Agnostic Transparent Checkpointing

Transparently checkpointing MPI for fault tolerance and load balancing is a long-standing problem in HPC. The problem has been complicated by the need to provide checkpoint-restart services for all combinations of an MPI implementation over all network interconnects. This work presents MANA (MPI-Agnostic Network-Agnostic transparent checkpointing), a single code base which supports all MPI implementation and interconnect combinations. The agnostic properties imply that one can checkpoint an MPI application under one MPI implementation and perhaps over TCP, and then restart under a second MPI implementation over InfiniBand on a cluster with a different number of CPU cores per node. This technique is based on a novel "split-process" approach, which enables two separate programs to co-exist within a single process with a single address space. This work overcomes the limitations of the two most widely adopted transparent checkpointing solutions, BLCR and DMTCP/InfiniBand, which require separate modifications to each MPI implementation and/or underlying network API. The runtime overhead is found to be insignificant both for checkpoint-restart within a single host, and when comparing a local MPI computation that was migrated to a remote cluster against an ordinary MPI computation running natively on that same remote cluster.
A comprehensive survey on networking over TV white spaces

Abstract TV white spaces refer to the allocated but locally unused TV spectrum and can be used by unlicensed devices as secondary users. Thanks to their lower frequencies (e.g., 54–698 MHz in the US), communication over the TV spectrum has excellent propagation characteristics over long distances and through obstacles. These characteristics along with their wide availability make the TV white spaces a great choice and alternative to many existing wireless technologies, especially the ones that need long range and high bandwidth communication. In the last decade, there have been numerous efforts from academia, industries, and standards bodies for exploiting the potentials of the TV white spaces for several applications including wireless broadband Internet access. Their characteristics and features also hold potentials for many new applications including sensing and monitoring, Internet of Things, wireless control, smart utility, location-based services, and transportation and logistics. In this paper, we perform a retrospective review and comparative study of existing work on networking in the TV white spaces. Additionally, we discuss the associated research challenges such as dealing with the interference between primary and secondary TV spectrum users, TV white space temporal and spatial variations and fragmentation, antenna design, mobility, and security. We also describe the future research directions to handle the above challenges. To the best of our knowledge, this is the first comprehensive survey on the literature of TV white space networking research.
Network Formation under Random Attack and Probabilistic Spread

We study a network formation game where agents receive benefits by forming connections to other agents but also incur both direct and indirect costs from the formed connections. Specifically, once the agents have purchased their connections, an attack starts at a randomly chosen vertex in the network and spreads according to the independent cascade model with a fixed probability, destroying any infected agents. The utility or welfare of an agent in our game is defined to be the expected size of the agent's connected component post-attack minus her expenditure in forming connections. Our goal is to understand the properties of the equilibrium networks formed in this game. Our first result concerns the edge density of equilibrium networks. A network connection increases both the likelihood of remaining connected to other agents after an attack as well the likelihood of getting infected by a cascading spread of infection. We show that the latter concern primarily prevails and any equilibrium network in our game contains only $O(n\log n)$ edges where $n$ denotes the number of agents. On the other hand, there are equilibrium networks that contain $\Omega(n)$ edges showing that our edge density bound is tight up to a logarithmic factor. Our second result shows that the presence of attack and its spread through a cascade does not significantly lower social welfare as long as the network is not too dense. We show that any non-trivial equilibrium network with $O(n)$ edges has $\Theta(n^2)$ social welfare, asymptotically similar to the social welfare guarantee in the game without any attacks.
Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control

Selective rationalization has become a common mechanism to ensure that predictive models reveal how they use any available features. The selection may be soft or hard, and identifies a subset of input features relevant for prediction. The setup can be viewed as a co-operate game between the selector (aka rationale generator) and the predictor making use of only the selected features. The co-operative setting may, however, be compromised for two reasons. First, the generator typically has no direct access to the outcome it aims to justify, resulting in poor performance. Second, there’s typically no control exerted on the information left outside the selection. We revise the overall co-operative framework to address these challenges. We introduce an introspective model which explicitly predicts and incorporates the outcome into the selection process. Moreover, we explicitly control the rationale complement via an adversary so as not to leave any useful information out of the selection. We show that the two complementary mechanisms maintain both high predictive accuracy and lead to comprehensive rationales.
English dictionary searching with little extra space

When text is typeset using a computer-based system, it can also be checked for spelling errors automatically and efficiently. Several methods of spelling error detection have been proposed. Morris et al. [MORR75] study statistical properties of English words, and describe an algorithm to catch possible typos by examining the relative frequency of trigrams (3-letter combinations). Kernighan et al. [KERN78] report a more conventional approach which looks up each word in a machine readable spelling dictionary. 1 Knuth [KNUT73] comments on dictionary storage, and suggests an organization intended to reduce space requirements. Another, somewhat unsophisticated technique sorts all words in a document and prints those which occur infrequently. Of course, habitually misspelled words escape unnoticed in a frequency based system.
Late-stage educational inequality: Can selection on noncognitive skills explain waning social background effects?

Abstract Past research finds that the effect of socioeconomic origin on the probability of making educational transitions decreases over the educational career from primary to graduate school. Some have argued that this pattern of waning is the result of selective attrition, since those of modest social origins who make a given transition may have exceptional cognitive or noncognitive skills while more advantaged individuals may rely less heavily on these skills to continue their education. We study a sample of American 10th graders from 1980 to assess how much the pattern of waning effects is due to selective attrition along noncognitive skills for this cohort. We find that controlling for noncognitive skills does not make the effect of socioeconomic origin more stable across transitions. Still, socioeconomic advantage does not decline uniformly across transitions, and it appears most pronounced at the transition into college, whether accounting for noncognitive skills or not. Our results suggest that origins continue to drive educational attainment even among those who make it to postsecondary transitions.
Effects of isothermal stratification strength on vorticity dynamics for single-mode compressible Rayleigh-Taylor instability

The effects of initial stratification on single-mode Rayleigh-Taylor instability are examined using fully compressible wavelet-based direct numerical simulations. Such instabilities are widespread and are found in inertial confinement fusion, supernova ignition fronts, x-ray bursts, and geophysics.
Hardy-Muckenhoupt Bounds for Laplacian Eigenvalues.

We present two graph quantities Psi(G,S) and Psi_2(G) which give constant factor estimates to the Dirichlet and Neumann eigenvalues, lambda(G,S) and lambda_2(G), respectively. Our techniques make use of a discrete Hardy-type inequality.
CupQ: A New Clinical Literature Search Engine

A new clinical literature search engine, called CupQ, is presented. It aims to help clinicians stay updated with medical knowledge. Although PubMed is currently one of the most widely used digital libraries for biomedical information, it frequently does not return clinically relevant results. CupQ utilizes a ranking algorithm that filters non-medical journals, compares semantic similarity between queries, and incorporates journal impact factor and publication date. It organizes search results into useful categories for medical practitioners: reviews, guidelines, and studies. Qualitative comparisons suggest that CupQ may return more clinically relevant information than PubMed. CupQ is available at https://cupq.io/.
History Dependence, Cohort Attachment, and Job Referrals in Networks of Close Relationships

Abstract We model network formation in a firm. Agents learn about the quality of their working relationships with each other. Their good relationships become their networks. Accumulating relationships becomes increasingly costly, however. Over time agents become less open to forming relationships with others unknown to them, leading their networks to be front-loaded with agents they met near the beginning of their careers. The interaction of this dynamic with turnover yields predictions about the time pattern of history dependence in an agent’s network as a function of his tenure. Mutual openness of newly arrived agents in a firm also leads to the cross-section prediction of “cohort attachment,” a tendency for members of an agent’s hiring cohort to be disproportionately represented in his network. When members of a network formed within a firm are subsequently split across many firms, the desire to renew their successful working relationships can lead to job referrals. Former co-workers who provide referrals will be drawn disproportionately from the referred workers’ hiring cohorts at their previous employers.
Police Performance As Symbolic Politics? Public Recognition and the Value of Awards

What constitutes “good” performance in a law enforcement agency, who decides, and how does public recognition of that performance change how an agency performs? This study uses a quasi-experimental...
Newton polytopes in algebraic combinatorics

A polynomial has saturated Newton polytope (SNP) if every lattice point of the convex hull of its exponent vectors corresponds to a monomial. We compile instances of SNP in algebraic combinatorics (some with proofs, others conjecturally): skew Schur polynomials; symmetric polynomials associated to reduced words, Redfield–Polya theory, Witt vectors, and totally nonnegative matrices; resultants; discriminants (up to quartics); Macdonald polynomials; key polynomials; Demazure atoms; Schubert polynomials; and Grothendieck polynomials, among others. Our principal construction is the Schubitope. For any subset of $$[n]^2$$, we describe it by linear inequalities. This generalized permutahedron conjecturally has positive Ehrhart polynomial. We conjecture it describes the Newton polytope of Schubert and key polynomials. We also define dominance order on permutations and study its poset-theoretic properties.
A Stereolithographically Fabricated Polymethacrylate Broadband THz Absorber

Additive manufactured THz optics have been introduced as an efficient alternative to their commercial counterparts. Among various additive manufacturing methods, stereolithography provides superior spatial resolution and surface finish. However, examples of stereolithographically fabricated components for THz applications are still scarce. In this paper, we report on the fabrication process and performance of a stereolithographically fabricated broadband absorber for the THz spectral range. Simple THz transmission experiments were carried out for the absorber and bulk reference samples. The experimental results indicated that the fabricated absorber effectively absorbs incident signal in the investigated THz spectral range.
Public-private partnership as remedy for crumbling infrastructure: Is this hope looking for reason?

It has become commonplace to describe publicly provided infrastructure as being in a sorry state and to advance public-private partnership as a possible remedy. This essay adopts a skeptical but not a cynical posture toward those claims. The paper starts by reviewing the comparative properties of markets and politics within a theory of budgeting where the options are construction and maintenance. This analytical point of departure explains how incongruities between political and market action can favor construction over maintenance. In short, political entities can engage in an implicit form of public debt by reducing maintenance spending to support other budgetary items. This implicit form of public debt does not manifest in higher interest rates but rather manifests in crumbling bridges and other infrastructure due to the transfer of maintenance into other budgetary activities.
Nonlinear study of spheromak tilt instability

The magnetohydrodynamic (MHD) tilt mode of a spheromak is thought to be the dominant unstable mode. In the present ^ study we attempt to apply our novel approximate Riemann solver for the threedimensional MHD equations to the analysis of the tilt instability of a spheromak contained in a prolate cylindrical vessel (flux conserver). We have applied an initial velocity perturbation to the spheromak and analyzed its evolution. The results are encouraging and the simulation shows that the spheromak tilts and evolves towards a minimum-energy state.
Genome-wide synthetic lethal CRISPR screen identifies FIS1 as a genetic interactor of ALS-linked C9ORF72.

Abstract Mutations in the C9ORF72 gene are the most common cause of amyotrophic lateral sclerosis (ALS). Both toxic gain of function and loss of function pathogenic mechanisms have been proposed. Accruing evidence from mouse knockout studies point to a role for C9ORF72 as a regulator of immune function. To provide further insight into its cellular function, we performed a genome-wide synthetic lethal CRISPR screen in human myeloid cells lacking C9ORF72. We discovered a strong synthetic lethal genetic interaction between C9ORF72 and FIS1, which encodes a mitochondrial membrane protein involved in mitochondrial fission and mitophagy. Mass spectrometry experiments revealed that in C9ORF72 knockout cells, FIS1 strongly bound to a class of immune regulators that activate the receptor for advanced glycation end (RAGE) products and trigger inflammatory cascades. These findings present a novel genetic interactor for C9ORF72 and suggest a compensatory role for FIS1 in suppressing inflammatory signaling in the absence of C9ORF72.
Emerging material systems for integrated optical Kerr frequency combs

The experimental realization of a Kerr frequency comb represented the convergence of research in materials, physics, and engineering. This symbiotic relationship continues to underpin efforts in comb innovation today. While the initial focus developing cavity-based frequency combs relied on existing microresonator architectures and classic optical materials, in recent years, this trend has been disrupted. This paper reviews the latest achievements in frequency comb generation using resonant cavities, placing them within the broader historical context of the field. After presenting well-established material systems and device designs, the emerging materials and device architectures are examined. Specifically, the unconventional material systems as well as atypical device designs that have enabled tailored dispersion profiles and improved comb performance are compared to the current state of art. The remaining challenges and outlook for the field of cavity-based frequency combs are evaluated.
Quantifying the success of measles vaccination campaigns in the Rohingya refugee camps

In the wake of the Rohingya population's mass migration from Myanmar, one of the world's largest refugee settlements was constructed in Cox's Bazar, Bangladesh to accommodate nearly 900,000 new refugees. Refugee populations are particularly vulnerable to infectious disease outbreaks due to many population and environmental factors. A large measles outbreak, with over 1700 cases, occurred among the Rohingya population between September and November 2017. Here, we estimate key epidemiological parameters and use a dynamic mathematical model of measles transmission to evaluate the effectiveness of the reactive vaccination campaigns in the refugee camps. We also estimate the potential for subsequent outbreaks under different vaccination coverage scenarios. Our modeling results highlight the success of the vaccination campaigns in rapidly curbing transmission and emphasize the public health importance of maintaining high levels of vaccination in this population, where high birth rates and historically low vaccination coverage rates create suitable conditions for future measles outbreaks.
A tunable ferroelectric based unreleased RF resonator.

This paper introduces the first tunable ferroelectric capacitor (FeCAP)-based unreleased RF MEMS resonator, integrated seamlessly in Texas Instruments’ 130 nm Ferroelectric RAM (FeRAM) technology. The designs presented here are monolithically integrated in solid-state CMOS technology, with no post-processing or release step typical of other MEMS devices. An array of FeCAPs in this complementary metal-oxide-semiconductor (CMOS) technology’s back-end-of-line (BEOL) process were used to define the acoustic resonance cavity as well as the electromechanical transducers. To achieve high quality factor (Q) of the resonator, acoustic waveguiding for vertical confinement within the CMOS stack is studied and optimized. Additional design considerations are discussed to obtain lateral confinement and suppression of spurious modes. An FeCAP resonator is demonstrated with fundamental resonance at 703 MHz and Q of 1012. This gives a frequency-quality factor product $$f \cdot Q = 7.11 \times 10^{11}$$ which is 1.6× higher than the most state-of-the-art Pb(Zr,Ti)O3 (PZT) resonators. Due to the ferroelectric characteristics of the FeCAPs, transduction of the resonator can be switched on and off by adjusting the electric polarization. In this case, the resonance can be turned off completely at ±0.3 V corresponding to the coercive voltage of the constituent FeCAP transducers. These novel switchable resonators may have promising applications in on-chip timing, ad-hoc radio front ends, and chip-scale sensors. A reinvention of memory technology from Texas Instruments has enabled the creation of high-efficiency, high-quality resonators. Microscopic radio frequency (RF) resonators vibrate at stable frequencies, a property that can be used in tracking time, communicating, sensing, and imaging. Technological advances are demanding smaller, more power-efficient and cost-effective components, but traditional resonators are reaching their theoretical limits. Dana Weinstein and her team from the United States’ Purdue University and Texas Instruments have developed a new resonator integrated into existing chip fabrication with no post-processing, and offers much higher quality factor than alternate devices made side by side with electronic circuits. In this new paper, the team discusses the optimization that produced these low loss vibrations, and how the resonance can be manipulated by adjusting the electric polarization of the device.
Hamiltonicity in randomly perturbed hypergraphs

Abstract For integers k ≥ 3 and 1 ≤ l ≤ k − 1 , we prove that for any α > 0 , there exist ϵ > 0 and C > 0 such that for sufficiently large n ∈ ( k − l ) N , the union of a k-uniform hypergraph with minimum vertex degree α n k − 1 and a binomial random k-uniform hypergraph G ( k ) ( n , p ) with p ≥ n − ( k − l ) − ϵ for l ≥ 2 and p ≥ C n − ( k − 1 ) for l = 1 on the same vertex set contains a Hamiltonian l-cycle with high probability. Our result is best possible up to the values of ϵ and C and answers a question of Krivelevich, Kwan and Sudakov.
An input–output based analysis of convective velocity in turbulent channels

This paper employs an input–output based approach to analyse the convective velocities and transport of fluctuations in turbulent channel flows. The convective velocity for a fluctuating quantity associated with streamwise–spanwise wavelength pairs at each wall-normal location is obtained through the maximization of the power spectral density associated with the linearized Navier–Stokes equations with a turbulent mean profile and delta-correlated Gaussian forcing. We first demonstrate that the mean convective velocities computed in this manner agree well with those reported previously in the literature. We then exploit the analytical framework to probe the underlying mechanisms contributing to the local convective velocity at different wall-normal locations by isolating the contributions of each streamwise–spanwise wavelength pair (flow scale). The resulting analysis suggests that the behaviour of the convective velocity in the near-wall region is influenced by large-scale structures further away from the wall. These structures resemble Townsend’s attached eddies in the cross-plane, yet show incomplete similarity in the streamwise direction. We then investigate the role of each linear term in the momentum equation to isolate the contribution of the pressure, mean shear, and viscous effects to the deviation of the convective velocity from the mean at each flow scale. Our analysis highlights the role of the viscous effects, particularly in regards to large channel spanning structures whose influence extends to the near-wall region. The results of this work suggest the promise of an input–output approach for analysing convective velocity across a range of flow scales using only the mean velocity profile.
Extended-range statistical ENSO prediction through operator-theoretic techniques for nonlinear dynamics.

Forecasting the El Nino-Southern Oscillation (ENSO) has been a subject of vigorous research due to the important role of the phenomenon in climate dynamics and its worldwide socioeconomic impacts. Over the past decades, numerous models for ENSO prediction have been developed, among which statistical models approximating ENSO evolution by linear dynamics have received significant attention owing to their simplicity and comparable forecast skill to first-principles models at short lead times. Yet, due to highly nonlinear and chaotic dynamics (particularly during ENSO initiation), such models have limited skill for longer-term forecasts beyond half a year. To resolve this limitation, here we employ a new nonparametric statistical approach based on analog forecasting, called kernel analog forecasting (KAF), which avoids assumptions on the underlying dynamics through the use of nonlinear kernel methods for machine learning and dimension reduction of high-dimensional datasets. Through a rigorous connection with Koopman operator theory for dynamical systems, KAF yields statistically optimal predictions of future ENSO states as conditional expectations, given noisy and potentially incomplete data at forecast initialization. Here, using industrial-era Indo-Pacific sea surface temperature (SST) as training data, the method is shown to successfully predict the Nino 3.4 index in a 1998–2017 verification period out to a 10-month lead, which corresponds to an increase of 3–8 months (depending on the decade) over a benchmark linear inverse model (LIM), while significantly improving upon the ENSO predictability “spring barrier”. In particular, KAF successfully predicts the historic 2015/16 El Nino at initialization times as early as June 2015, which is comparable to the skill of current dynamical models. An analysis of a 1300-yr control integration of a comprehensive climate model (CCSM4) further demonstrates that the enhanced predictability afforded by KAF holds over potentially much longer leads, extending to 24 months versus 18 months in the benchmark LIM. Probabilistic forecasts for the occurrence of El Nino/La Nina events are also performed and assessed via information-theoretic metrics, showing an improvement of skill over LIM approaches, thus opening an avenue for environmental risk assessment relevant in a variety of contexts.
Let's talk sooner rather than later: The strategic communication decisions of activist blockholders

Abstract When starting their campaigns, activist investors face the decision of when to begin communication with the management of the target firm. We document how the choice to start communication early with management, before the 13D disclosure, fits within the campaign's overall strategy. Nearly a quarter of the activist campaigns in our sample begin with what we call open activism. More credible activists with lower costs of activism are more likely to engage with management early and this early engagement is related to their desire to see specific changes made at the target firm. Eventual actions taken by activists, such as a subsequent merger or proxy contest, as well as the long-run performance of the target, are also related to this initial communication decision. Together, our findings suggest that open activism is an important part of the activist's underlying strategy and that market participants understand this link.
Correlation between retinal ganglion cell loss and nerve crush force-impulse established with instrumented tweezers in mice

Objectives: Rodent models of optic nerve crush (ONC) have often been used to study degeneration and regeneration of retinal ganglion cells (RGCs) and their axons as well as the underlying molecular mechanisms. However, ONC results from different laboratories exhibit a range of RGC injury with varying degree of axonal damage. We developed instrumented tweezers to measure optic nerve (ON) crush forces in real time and studied the correlation between RGC axon loss and force-impulse, the product of force and duration, applied through the instrumented tweezers in mice.Methods: A pair of standard self-closing #N7 tweezers were instrumented with miniature foil strain gauges at optimal locations on both tweezers' arms. The instrumented tweezers were capable of recording the tip closure forces in the form of voltages, which were calibrated through load cells to corresponding tip closure forces over the operating range. Using the instrumented tweezers, the ONs of multiple mice were crushed with varied forces and durations and the axons in the immunostained sections of the crushed ONs were counted.Results: We found that the surviving axon density correlated with crush force, with longer duration and stronger crush forces producing consistently more axon damage.Discussion: The instrumented tweezers enable a simple technique for measurement of ONC forces in real-time for the first time. Using the instrumented tweezers, experimenters can quantify crush forces during ONC to produce consistent and predictable post-crush cell death. This should permit future studies a way to produce nerve damage more consistently than is available now.
Experts, but not novices, exhibit StartReact indicating experts use the reticulospinal system more than novices

Motor skill acquisition utilizes a wide array of neural structures; however, few articles evaluate how the relative contributions of these structures shift over the course of learning. Recent evide...
Second-Best Beam-Alignment via Bayesian Multi-Armed Bandits

Millimeter-wave (mm-wave) systems rely on narrow-beams to cope with the severe signal attenuation in the mm-wave frequency band. However, susceptibility to beam mis- alignment due to mobility or blockage requires the use of beam-alignment schemes, with huge cost in terms of overhead and use of system resources. In this paper, a beam-alignment scheme is proposed based on Bayesian multi-armed bandits, with the goal to maximize the alignment probability and the data-communication throughput. A Bayesian approach is proposed, by considering the state as a posterior distribution over angles of arrival (AoA) and of departure (AoD), given the history of feedback signaling and of beam pairs scanned by the base- station (BS) and the user-end (UE). A simplified sufficient statistic for optimal control is identified, in the form of preference of BS-UE beam pairs. By bounding a value function, the second-best preference policy is formulated, which strikes an optimal balance between exploration and exploitation by selecting the beam pair with the current second-best preference. Through Monte-Carlo simulation with analog beamforming, the superior performance of the second-best preference policy is demonstrated in comparison to existing schemes based on first-best preference, linear Thompson sampling, and upper confidence bounds, with up to 7%, 10% and 30% improvements in alignment probability, respectively.
Interaction of biased electrodes and plasmas: sheaths, double layers, and fireballs

Biased electrodes are common components of plasma sources and diagnostics. The plasma-electrode interaction is mediated by an intervening sheath structure that influences properties of the electrons and ions contacting the electrode surface, as well as how the electrode influences properties of the bulk plasma. A rich variety of sheath structures have been observed, including ion sheaths, electron sheaths, double sheaths, double layers, anode glow, and fireballs. These represent complex self-organized responses of the plasma that depend not only on the local influence of the electrode, but also on the global properties of the plasma and the other boundaries that it is in contact with. This review summarizes recent advances in understanding the conditions under which each type of sheath forms, what the basic stability criteria and steady-state properties of each are, and the ways in which each can influence plasma-boundary interactions and bulk plasma properties. These results may be of interest to a number of application areas where biased electrodes are used, including diagnostics, plasma modification of materials, plasma sources, electric propulsion, and the interaction of plasmas with objects in space.
Exact sequences on Powell–Sabin splits

We construct smooth finite elements spaces on Powell–Sabin triangulations that form an exact sequence. The first space of the sequence coincides with the classical $$C^1$$ Powell–Sabin space, while the others form stable and divergence-free yielding pairs for the Stokes problem. We develop degrees of freedom for these spaces that induce projections that commute with the differential operators.