cssi/SciSciGPT-SciSciNet huggingface dataset:
Replica symmetry in upper tails of mean-field hypergraphs

Abstract Given a sequence of s-uniform hypergraphs { H n } n ≥ 1 , denote by T p ( H n ) the number of edges in the random induced hypergraph obtained by including every vertex in H n independently with probability p ∈ ( 0 , 1 ) . Recent advances in the large deviations of low complexity non-linear functions of independent Bernoulli variables can be used to show that tail probabilities of T p ( H n ) are precisely approximated by the so-called ‘mean-field’ variational problem, under certain assumptions on the sequence { H n } n ≥ 1 . In this paper, we study properties of this variational problem for the upper tail of T p ( H n ) , assuming that the mean-field approximation holds. In particular, we show that the variational problem has a universal replica symmetric phase (where it is uniquely minimized by a constant function), for any sequence of regular s-uniform hypergraphs, which depends only on s. We also analyze the associated variational problem for the related problem of estimating subgraph frequencies in a converging sequence of dense graphs. Here, the variational problems themselves have a limit which can be expressed in terms of the limiting graphon, which gives the exact Bahadur slope of the corresponding estimate.
The Orphan Tsunami of 1700. Japanese Clues to a Parent Earthquake in North America

[Title in Japanese: The Orphan Tsunami of the Genroku Era], in English and in Japanese, by B.F. Atwater, S. Musumi‐Rokkaku, K. Satake, Y. Tsuji, K. Ueda and D.K. Yamaguchi, US Geological Survey, Re...
Collusion over the Business Cycle

We present a theory of collusive pricing for markets in which demand alternates stochastically between fast-growth (boom) and slow-growth (recession) phases. We show that (1) the most-collusive prices are weakly procyclical (countercyclical) when demand growth rates are positively (negatively) correlated through time, and (2) the amplitude of the collusive pricing cycle is larger when the expected duration of boom phases decreases and when the expected duration of recession phases increases. We also offer a generalization of Rotemberg and Saloner's (1986) model, interpreting their findings in terms of transitory demand shocks that occur within broader business cycle phases.
How effective is macroprudential policy? Evidence from lending restriction measures in EU countries

Abstract This 2 paper assesses the effectiveness of lending restrictions measures, such as loan-to-value and debt-service-to-income ratios, in affecting developments in house prices and credit. We use data on 99 lending standard restrictions implemented in 28 EU countries over 1990–2018. The results suggest that lending restriction measures are generally effective in curbing house prices and credit. However, the impact is delayed and reaches its peak only after three years. In addition, the impact is asymmetric, with tightening measures having weaker association with target variables compared to loosening measures. The association is stronger in countries outside of euro area and for legally-binding measures and measures involving sanctions. The results have practical implications for macroprudential authorities.
Chromatic number, induced cycles, and non-separating cycles

We study two parameters obtained from the Euler characteristic by replacing the number of faces with that of induced and induced non-separating cycles. By establishing monotonicity of such parameters under certain homomorphism and edge contraction, we obtain new upper bounds on the chromatic number in terms of the number of induced cycles and the Hadwiger number in terms of the number of induced non-separating cycles. As an application, we show that every 3-connected graph with average degree at least 2k for some $$k\ge 2$$ have at least $$(k-1)|V|+Ck^{3}\log ^{3/2}k$$ induced non-separating cycles for some explicit constant $$C>0$$ . This improves the previous best known lower bound $$(k-1)|V|+1$$ , which follows from Tutte’s cycle space theorem. We also give a short proof of this theorem of Tutte.
Multistring based matrices

A virtualn-string is a chord diagram with n core circles and a collection of arrows between core circles. We consider virtual n-strings up to virtual homotopy, compositions of flat virtual Reidemei...
Social welfare and price of anarchy in preemptive priority queues

Abstract Consider an unobservable M | G | 1 queue with preemptive-resume scheduling and two priority classes. Customers are strategic and may join the premium class for a fee. We analyze the resulting equilibrium outcomes, equilibrium stability, and social welfare. We find that for service distributions with coefficient of variation greater than 1, there exists a unique and stable mixed equilibrium at low loads. We also establish a tight bound on the price of anarchy, which is 4 ∕ 3 .
Discrete Action On-Policy Learning with Action-Value Critic

Reinforcement learning (RL) in discrete action space is ubiquitous in real-world applications, but its complexity grows exponentially with the action-space dimension, making it challenging to apply existing on-policy gradient based deep RL algorithms efficiently. To effectively operate in multidimensional discrete action spaces, we construct a critic to estimate action-value functions, apply it on correlated actions, and combine these critic estimated action values to control the variance of gradient estimation. We follow rigorous statistical analysis to design how to generate and combine these correlated actions, and how to sparsify the gradients by shutting down the contributions from certain dimensions. These efforts result in a new discrete action on-policy RL algorithm that empirically outperforms related on-policy algorithms relying on variance control techniques. We demonstrate these properties on OpenAI Gym benchmark tasks, and illustrate how discretizing the action space could benefit the exploration phase and hence facilitate convergence to a better local optimal solution thanks to the flexibility of discrete policy.
Fast Risk Assessment for Autonomous Vehicles Using Learned Models of Agent Futures.

This paper presents fast non-sampling based methods to assess the risk of trajectories for autonomous vehicles when probabilistic predictions of other agents' futures are generated by deep neural networks (DNNs). The presented methods address a wide range of representations for uncertain predictions including both Gaussian and non-Gaussian mixture models for predictions of both agent positions and controls. We show that the problem of risk assessment when Gaussian mixture models (GMMs) of agent positions are learned can be solved rapidly to arbitrary levels of accuracy with existing numerical methods. To address the problem of risk assessment for non-Gaussian mixture models of agent position, we propose finding upper bounds on risk using Chebyshev's Inequality and sums-of-squares (SOS) programming; they are both of interest as the former is much faster while the latter can be arbitrarily tight. These approaches only require statistical moments of agent positions to determine upper bounds on risk. To perform risk assessment when models are learned for agent controls as opposed to positions, we develop TreeRing, an algorithm analogous to tree search over the ring of polynomials that can be used to exactly propagate moments of control distributions into position distributions through nonlinear dynamics. The presented methods are demonstrated on realistic predictions from DNNs trained on the Argoverse and CARLA datasets and are shown to be effective for rapidly assessing the probability of low probability events.
Social capital and capital structure

The nature of how capital structure can affect firm value is often investigated in the discipline of financial economics. Less investigated is how the nature of the type of assets can affect the ch...
Artemisia annua and Artemisia afra extracts exhibit strong bactericidal activity against Mycobacterium tuberculosis.

Abstract Ethnopharmacological relevance Emergence of drug-resistant and multidrug-resistant Mycobacterium tuberculosis (Mtb) strains is a major barrier to tuberculosis (TB) eradication, as it leads to longer treatment regimens and in many cases treatment failure. Thus, there is an urgent need to explore new TB drugs and combinations, in order to shorten TB treatment and improve outcomes. Here, we evaluated the potential of two Asian and African traditional medicinal plants, Artemisia annua, a natural source of artemisinin (AN), and Artemisia afra, as sources of novel antitubercular agents. Aim of the study Our goal was to measure the activity of A. annua and A. afra extracts against Mtb as potential natural and inexpensive therapies for TB treatment, or as sources of compounds that could be further developed into effective treatments. Materials and methods The minimum inhibitory concentrations (MICs) of A. annua and A. afra dichloromethane extracts were determined, and concentrations above the MICs were used to evaluate their ability to kill Mtb and Mycobacterium abscessus in vitro. Results Previous studies showed that A. annua and A. afra inhibit Mtb growth. Here, we show for the first time that Artemisia extracts have a strong bactericidal activity against Mtb. The killing effect of A. annua was much stronger than equivalent concentrations of pure AN, suggesting that A. annua extracts kill Mtb through a combination of AN and additional compounds. A. afra, which produces very little AN, displayed bactericidal activity against Mtb that was substantial but weaker than that of A. annua. In addition, we measured the activity of Artemisia extracts against Mycobacterium abscessus. Interestingly, we observed that while A. annua is not bactericidal, it inhibits growth of M. abscessus, highlighting the potential of this plant in combinatory therapies to treat M. abscessus infections. Conclusion Our results indicate that Artemisia extracts have an enormous potential for treatment of TB and M. abscessus infections, and that these plants contain bactericidal compounds in addition to AN. Combination of extracts with existing antibiotics may not only improve treatment outcomes but also reduce the emergence of resistance to other drugs.
On Optimality of CSS Codes for Transversal T

In order to perform universal fault-tolerant quantum computation, one needs to implement a logical non-Clifford gate. Consequently, it is important to understand codes that implement such gates transversally. In this paper, we adopt an algebraic approach to characterize all stabilizer codes for which transversal $T$ and $T^{\dagger }$ gates preserve the codespace. Our Heisenberg perspective reduces this question to a finite geometry problem that translates to the design of certain classical codes. We prove three corollaries of this result: (a) For any non-degenerate $[\![n,k,d]\!]$ stabilizer code supporting a physical transversal $T$ (which might not be logical $T$ ), there exists an $[\![n,k,d]\!]$ CSS code with the same property; (b) Triorthogonal codes form the most general family of CSS codes that realize logical transversal $T$ via physical transversal $T$ ; (c) Triorthogonality is necessary for physical transversal $T$ on a CSS code to realize the logical identity. The main tool we use is a recent characterization of a particular family of diagonal gates in the Clifford hierarchy that are efficiently described by symmetric matrices over rings of integers [N. Rengaswamy et al. , Phys. Rev. A 100, 022304]. We refer to these operations as Quadratic Form Diagonal (QFD) gates. Our framework generalizes all existing stabilizer code constructions that realize logical gates via transversal $T$ . We provide several examples of codes and briefly discuss connections to decreasing monomial codes, pin codes, generalized triorthogonality and quasitransversality. We partially extend these results towards characterizing all stabilizer codes that support transversal $\pi /2^{\ell }~Z$ -rotations. In particular, using Ax’s theorem on residue weights of polynomials, we provide an alternate characterization of logical gates induced by transversal $\pi /2^{\ell }~Z$ -rotations on a family of quantum Reed-Muller codes. We also briefly discuss a general approach to analyze QFD gates that might lead to a characterization of all stabilizer codes that support any given physical transversal 1- or 2-local diagonal gate.
Towards a Sustainable Infrastructure for the Preservation of Cultural Heritage and Digital Scholarship

The digital lifecycle contains definitive processes of data curation, management, long-term preservation, and dissemination of the content, all key building blocks in the development of a digital library. It is vital to maintain a complete digital lifecycle workflow for the preservation of digital cultural heritage and digital scholarship. In this talk, I will explore a digital lifecycle program (DLP) [1] for digital libraries. When we begin to build a complete digital lifecycle, we also refer to the print lifecycle. The two are similar despite differences in format and physical conditions for content creation (selection & data mining, conversion and curation), organization (analysis, integration, aggregation and linking), and interpretation (metadata and cataloging), preservation (data storage, duplication, checksum & repair, and migration), access and publishing (navigating, discovery and rights management). Only through a systematic and sustainable digital lifecycle program, can we build platforms for cross disciplinary research and repositories of large aggregated digital content. DLP can be exemplified in specific cultural heritage projects such as the Digital Dunhuang project [2]. Digital Dunhuang enables long-term preservation of cultural heritage of inestimable value, while providing a platform for sharing all digital assets generated in the act of preservation. With the support of The Mellon Foundation, the Dunhuang Academy has been exploring building a permanent repository of all Digital Dunhuang assets. The only way to ensure that information gathered from Dunhuang's Mogao Caves is permanently preserved for future generations, is to integrate all the content that has been created in the past, is being created now, and will be created in the future into one large digital repository [3]. This digital repository will facilitate perpetual preservation, effective digital asset management operations, and easy access in a systematic way. In facilitating the digital lifecycle development, we are ensuring that knowledge and scholarship created in the digital age will be able to survive as print-and-paper scholarship has for centuries. We are also ensuring that the vast number of users of the digital library will have effective access to aggregated content across different domains and platforms. During those transformative changes, librarians will take on shifting roles in data management, digital preservation, rights management, open access, and innovation.
Augmented factor models with applications to validating market risk factors and forecasting bond risk premia

Abstract We study factor models augmented by observed covariates that have explanatory powers on the unknown factors. In financial factor models, the unknown factors can be reasonably well explained by a few observable proxies, such as the Fama–French factors. In diffusion index forecasts, identified factors are strongly related to several directly measurable economic variables such as consumption-wealth variable, financial ratios, and term spread. With those covariates, both the factors and loadings are identifiable up to a rotation matrix even only with a finite dimension. To incorporate the explanatory power of these covariates, we propose a smoothed or projected principal component analysis (PCA): (i) regress the data onto the observed covariates, and (ii) take the principal components of the fitted data to estimate the loadings and factors. This allows us to more accurately estimate the percentage of both explained and unexplained components in factors and thus to assess the explanatory power of covariates. We show that both the estimated factors and loadings can be estimated with improved rates of convergence compared to the benchmark method. The degree of improvement depends on the strength of the signals, representing the explanatory power of the covariates on the factors. The proposed estimator is robust to possibly heavy-tailed distributions. We apply the model to forecast US bond risk premia, and find that the observed macroeconomic characteristics contain strong explanatory powers of the factors. The gain of forecast is more substantial when the characteristics are incorporated to estimate the common factors than directly used for forecasts.
Thruster-assisted Center Manifold Shaping in Bipedal Legged Locomotion

This work tries to contribute to the design of legged robots with capabilities boosted through thrusterassisted locomotion. Our long-term goal is the development of robots capable of negotiating unstructured environments, including land and air, by leveraging legs and thrusters collaboratively. These robots could be used in a broad number of applications including search and rescue operations, space exploration, automated package handling in residential spaces and digital agriculture, to name a few. In all of these examples, the unique capability of thruster-assisted mobility greatly broadens the locomotion designs possibilities for these systems. In an effort to demonstrate thrusters effectiveness in the robustification and efficiency of bipedal locomotion gaits, this work explores their effects on the gait limit cycles and proposes new design paradigms based on shaping these center manifolds with strong foliations. Unilateral contact force feasibility conditions are resolved in an optimal control scheme.
Hybrid Precoding for mmWave Massive MIMO With One-Bit DAC

Hybrid beamforming is key to achieving energy-efficient 5G wireless networks equipped with massive amount of antennas. Low-resolution data converters bring yet another degree of freedom to energy efficiency for the state-of-the-art 5G transceivers. In this work, we consider the design of hybrid precoders for massive multiple-input multiple-output (MIMO) channels in millimeter-wave (mmWave) spectrum along with one-bit digital-to-analog converters (DACs) and finite-quantized phase shifters. In particular, we propose an alternating-optimization-based precoder design which recursively computes the covariance of the quantization distortion, and updates the precoders accordingly. Numerical results verify that the achievable rate improves quickly through iterations that involve updates to the weight matrix, distortion covariance of the quantization, and the respective precoders.
Three-Dimensional Single-Shot Ptychography

We introduce three-dimensional single-shot ptychography (3DSSP). 3DSSP implements a novel algorithm to reconstruct multiple 2D planes of a 3D object. We analyze the technique's performance via numerical simulations, and we demonstrate it experimentally.
Classical Coding Problem from Transversal T Gates

Universal quantum computation requires the implementation of a logical non-Clifford gate. In this paper, we characterize all stabilizer codes whose code subspaces are preserved under physical T and T† gates. For example, this could enable magic state distillation with non-CSS codes and, thus, provide better parameters than CSS-based protocols. However, among non-degenerate stabilizer codes that support transversal T, we prove that CSS codes are optimal. We also show that triorthogonal codes are, essentially, the only family of CSS codes that realize logical transversal T via physical transversal T. Using our algebraic approach, we reveal new purely-classical coding problems that are intimately related to the realization of logical operations via transversal T. Decreasing monomial codes are also used to construct a code that realizes logical CCZ. Finally, we use Ax’s theorem to characterize the logical operation realized on a family of quantum Reed-Muller codes. This result is generalized to finer angle Z-rotations in https://arxiv.org/abs/1910.09333.
A New High-Dimensional Quantum Entropic Uncertainty Relation with Applications

In this paper we derive a new quantum entropic uncertainty relation, bounding the conditional smooth quantum min entropy based on the result of a measurement using a two outcome POVM and the failure probability of a classical sampling strategy. Our relation works for systems of arbitrary dimension. We apply it to analyze a new source independent quantum random number generation protocol and show our relation provides optimistic results compared to prior work.
Microparticle impact-bonding modes for mismatched metals: From co-deformation to splatting and penetration

Abstract We present a comprehensive experimental campaign of high-velocity microparticle impacts with different combinations of particle and substrate materials to identify possible deformation regimes. Based on experimental observations of the impact sites, we identify three typical modes of behavior, namely, splatting, co-deformation, and penetration. We develop a theoretical framework to predict the operative regime for a given particle/substrate combination, ranging from splatting and penetration at two extremes of a spectrum, and co-deformation in the center. We propose an impact ratio based on the materials’ properties, which can successfully quantify the spectrum. Co-deformation is expected when the ratio is around unity, while much larger or smaller ratios give rise to penetration and splatting, respectively.
Field Experiment on the Profit Implications of Merchants’ Discretionary Power to Override Data-Driven Decision-Making Tools

Data-driven decision-making (DDD) is rapidly transforming modern operations. The availability of big data, advances in data analytics tools, and rapid gains in processing power enable firms to make...
Video-Capable Ultrasonic Wireless Communications Through Biological Tissues

The use of wireless implanted medical devices (IMDs) is growing because they facilitate monitoring of patients at home and during normal activities, reduce the discomfort of patients, and reduce the likelihood of infection associated with trailing wires. Currently, radio frequency (RF) electromagnetic waves are the most commonly used method for communicating wirelessly with IMDs. However, due to the restrictions on the available bandwidth and the employable power, data rates of RF-based IMDs are limited to 267 kb/s. Considering standard definition video streaming requires data rates of 1.2 Mb/s and high definition requires 3 Mb/s, it is not possible to use the RF electromagnetic communications for high data rate communication applications such as video streaming. In this work, an alternative method that utilizes ultrasonic waves to relay information at high data rates is introduced. An advanced quadrature amplitude modulation (QAM) modem with phase-compensating, sparse decision feedback equalizer (DFE) is tailored to realize the full potential of the ultrasonic channel through biological tissues. The proposed system is tested in a variety of scenarios, including both simulations with finite impulse response (FIR) channel models, and real physical transmission experiments with ex vivo beef liver and pork chop samples as well as in situ rabbit abdomen. Consequently, the simulations demonstrated that video-capable data rates can be achieved with millimeter-sized transducers. Real physical experiments confirmed data rates of 6.7, 4.4, 4, and 3.2 Mb/s through water, ex vivo beef liver, ex vivo pork chop, and in situ rabbit abdomen, respectively.
Dynamics of Contrast Decrement and Increment Responses in Human Visual Cortex.

Purpose The goal of the present experiments was to determine whether electrophysiologic response properties of the ON and OFF visual pathways observed in animal experimental models can be observed in humans. Methods Steady-state visual evoked potentials (SSVEPs) were recorded in response to equivalent magnitude contrast increments and decrements presented within a probe-on-pedestal Westheimer sensitization paradigm. The probes were modulated with sawtooth temporal waveforms at a temporal frequency of 3 or 2.73 Hz. SSVEP response waveforms and response spectra for incremental and decremental stimuli were analyzed as a function of stimulus size and visual field location in 67 healthy adult participants. Results SSVEPs recorded at the scalp differ between contrast decrements and increments of equal Weber contrast: SSVEP responses were larger in amplitude and shorter in latency for contrast decrements than for contrast increments. Both increment and decrement responses were larger for displays that were scaled for cortical magnification. Conclusions In a fashion that parallels results from the early visual system of cats and monkeys, two key properties of ON versus OFF pathways found in single-unit recordings are recapitulated at the population level of activity that can be observed with scalp electrodes, allowing differential assessment of ON and OFF pathway activity in human. Translational Relevance As data from preclinical models of visual pathway dysfunction point to differential damage to subtypes of retinal ganglion cells, this approach may be useful in future work on disease detection and treatment monitoring.
A modular chromosomally integrated toolkit for ectopic gene expression in Vibrio cholerae

The ability to express genes ectopically in bacteria is essential for diverse academic and industrial applications. Two major considerations when utilizing regulated promoter systems for ectopic gene expression are (1) the ability to titrate gene expression by addition of an exogenous inducer and (2) the leakiness of the promoter element in the absence of the inducer. Here, we describe a modular chromosomally integrated platform for ectopic gene expression in Vibrio cholerae. We compare the broadly used promoter elements Ptac and PBAD to versions that have an additional theophylline-responsive riboswitch (Ptac-riboswitch and PBAD-riboswitch). These constructs all exhibited unimodal titratable induction of gene expression, however, max induction varied with Ptac > PBAD > PBAD-riboswitch > Ptac-riboswitch. We also developed a sensitive reporter system to quantify promoter leakiness and show that leakiness for Ptac > Ptac-riboswitch > PBAD; while the newly developed PBAD-riboswitch exhibited no detectable leakiness. We demonstrate the utility of the tightly inducible PBAD-riboswitch construct using the dynamic activity of type IV competence pili in V. cholerae as a model system. The modular chromosomally integrated toolkit for ectopic gene expression described here should be valuable for the genetic study of V. cholerae and could be adapted for use in other species.
Detection-averse optimal and receding-horizon control for Markov decision processes

Abstract In this paper, we consider a Markov decision process (MDP) in which the ego agent intends to hide its state from detection by an adversary while pursuing a nominal objective. After formulating the detection-averse MDP problem, we first describe a value iteration (VI) approach to exactly solve it. To overcome the “curse of dimensionality” and thus gain scalability to larger-sized problems, we then propose a receding-horizon optimization (RHO) approach to compute approximate solutions. Numerical examples are reported to illustrate and compare the VI and RHO approaches, and show the potential of the proposed problem formulation for practical applications.
Bank liquidity provision across the firm size distribution

Abstract We use supervisory loan-level data to document that small firms (SMEs) obtain shorter maturity credit lines than large firms, post more collateral, have higher utilization rates, and pay higher spreads. We rationalize these facts as the equilibrium outcome of a trade-off between lender commitment and discretion. Using the COVID recession, we test the prediction that SMEs are subject to greater lender discretion. Consistent with this hypothesis, SMEs did not draw down whereas large firms did, even in response to similar demand shocks. PPP recipients reduced non-PPP loan balances, indicating the program bolstered their liquidity and alleviated the shortfall.
Plateau's problem as a singular limit of capillarity problems

Soap films at equilibrium are modeled, rather than as surfaces, as regions of small total volume through the introduction of a capillarity problem with a homotopic spanning condition. This point of view introduces a length scale in the classical Plateau's problem, which is in turn recovered in the vanishing volume limit. This approximation of area minimizing hypersurfaces leads to an energy based selection principle for Plateau's problem, points at physical features of soap films that are unaccessible by simply looking at minimal surfaces, and opens several challenging questions.
High-Dimensional Uncertainty Quantification via Active and Rank-Adaptive Tensor Regression

Uncertainty quantification based on stochastic spectral methods suffers from the curse of dimensionality. This issue was mitigated recently by low-rank tensor methods. However, there exist two fundamental challenges in low-rank tensor-based uncertainty quantification: how to automatically determine the tensor rank and how to pick the simulation samples. This paper proposes a novel tensor regression method to address these two challenges. Our method uses an $\ell_{2,p}$-norm regularization to determine the tensor rank and an estimated Voronoi diagram to pick informative samples for simulation. The proposed framework is verified by a 19-dim phonics bandpass filter and a 57-dim CMOS ring oscillator, capturing the high-dimensional uncertainty well with only 90 and 290 samples respectively.
On Front-End Gain Invariant Modeling for Wake Word Spotting.

Wake word (WW) spotting is challenging in far-field due to the complexities and variations in acoustic conditions and the environmental interference in signal transmission. A suite of carefully designed and optimized audio front-end (AFE) algorithms help mitigate these challenges and provide better quality audio signals to the downstream modules such as WW spotter. Since the WW model is trained with the AFE-processed audio data, its performance is sensitive to AFE variations, such as gain changes. In addition, when deploying to new devices, the WW performance is not guaranteed because the AFE is unknown to the WW model. To address these issues, we propose a novel approach to use a new feature called $\Delta$LFBE to decouple the AFE gain variations from the WW model. We modified the neural network architectures to accommodate the delta computation, with the feature extraction module unchanged. We evaluate our WW models using data collected from real household settings and showed the models with the $\Delta$LFBE is robust to AFE gain changes. Specifically, when AFE gain changes up to $\pm$12dB, the baseline CNN model lost up to relative 19.0% in false alarm rate or 34.3% in false reject rate, while the model with $\Delta$LFBE demonstrates no performance loss.
Entanglement Entropy and its Quench Dynamics for Pure States of the Sachdev-Ye-Kitaev model

Sachdev-Ye-Kitaev (SYK) is a concrete solvable model with non-Fermi liquid behavior and maximal chaos. In this work, we study the entanglement Renyi entropy for the subsystems of the SYK model in the Kourkoulou-Maldacena states. We use the path-integral approach and take the saddle point approximation in the large-N limit. We find a first-order transition exist when tuning the subsystem size for the q = 4 case, while it is absent for the q = 2 case. We further study the entanglement dynamics for such states under the real-time evolution for noninteracting, weakly interacting and strongly interacting SYK(-like) models.
Mapping Generative Models onto a Network of Digital Spiking Neurons

Stochastic neural networks such as Restricted Boltzmann Machines (RBMs) have been successfully used in applications ranging from speech recognition to image classification, and are particularly interesting because of their potential for generative tasks. Inference and learning in these algorithms use a Markov Chain Monte Carlo procedure called Gibbs sampling, where a logistic function forms the kernel of this sampler. On the other side of the spectrum, neuromorphic systems have shown great promise for low-power and parallelized cognitive computing, but lack well-suited applications and automation procedures. In this work, we propose a systematic method for bridging the RBM algorithm and digital neuromorphic systems, with a generative pattern completion task as proof of concept. For this, we first propose a method of producing the Gibbs sampler using bio-inspired digital noisy integrate-and-fire neurons. Next, we describe the process of mapping generative RBMs trained offline onto the IBM TrueNorth neurosynaptic processor—a low-power digital neuromorphic VLSI substrate. Mapping these algorithms onto neuromorphic hardware presents unique challenges in network connectivity and weight and bias quantization, which, in turn, require architectural and design strategies for the physical realization. Generative performance is analyzed to validate the neuromorphic requirements and to best select the neuron parameters for the model. Lastly, we describe a design automation procedure which achieves optimal resource usage, accounting for the novel hardware adaptations. This work represents the first implementation of generative RBM inference on a neuromorphic VLSI substrate.
Neutron star observations: Prognosis for equation of state constraints

Abstract We investigate how current and proposed observations of neutron stars can lead to an understanding of the state of their interiors and the key unknowns: the typical neutron star radius and the neutron star maximum mass. We consider observations made not only with photons, ranging from radio waves to X-rays, but also those involving neutrinos and gravity waves. We detail how precision determinations of structural properties would lead to significant restrictions on the poorly understood equation of state near and beyond the equilibrium density of nuclear matter. To begin, a theoretical analysis of neutron star structure, including general relativistic limits to mass, compactness, and spin rates is made. A review is the made of recent observations such as pulsar timing (which leads to mass, spin period, glitch and moment of inertia estimates), optical and X-ray observations of cooling neutron stars (which lead to estimates of core temperatures and ages and inferences about the internal composition), and X-ray observations of accreting and bursting sources (which shed light on both the crustal properties and internal composition). Next, we discuss neutrino emission from proto-neutron stars and how neutrino observations of a supernova, from both current and planned detectors, might impact our knowledge of the interiors, mass and radii of neutron stars. We also explore the question of how superstrong magnetic fields could affect the equation of state and neutron star structure. This is followed by a look at binary mergers involving neutron stars and how the detection of gravity waves could unambiguously distinguish normal neutron stars from self-bound strange quark matter stars.
Joint similarity to operators in noncommutative varieties

In this paper we solve several problems concerning joint similarity to n-tuples of operators in noncommutative varieties in $[B(\cH)^n]_1$ associated with positive regular free holomorphic functions in $n$ noncommuting variables and with sets of noncommutative polynomials in $n$ indeterminates, where $B(\cH)$ is the algebra of all bounded linear operators on a Hilbert space $\cH$. In particular, if $f=X_1+...+X_n$ and $\cP=\{0\}$, the elements of the corresponding variety can be seen as noncommutative multivariable analogues of Agler's $m$-hypercontractions.
Field testing of biohybrid robotic jellyfish to demonstrate enhanced swimming speeds

Biohybrid robotic designs incorporating live animals and self-contained microelectronic systems can leverage the animals’ own metabolism to reduce power constraints and act as natural chassis and actuators with damage tolerance. Previous work established that biohybrid robotic jellyfish can exhibit enhanced speeds up to 2.8 times their baseline behavior in laboratory environments. However, it remains unknown if the results could be applied in natural, dynamic ocean environments and what factors can contribute to large animal variability. Deploying this system in the coastal waters of Massachusetts, we validate and extend prior laboratory work by demonstrating increases in jellyfish swimming speeds up to 2.3 times greater than their baseline, with absolute swimming speeds up to 6.6 ± 0.3 cm s−1. These experimental swimming speeds are predicted using a hydrodynamic model with morphological and time-dependent input parameters obtained from field experiment videos. The theoretical model can provide a basis to choose specific jellyfish with desirable traits to maximize enhancements from robotic manipulation. With future work to increase maneuverability and incorporate sensors, biohybrid robotic jellyfish can potentially be used to track environmental changes in applications for ocean monitoring.
Anyonic entanglement and topological entanglement entropy

Abstract We study the properties of entanglement in two-dimensional topologically ordered phases of matter. Such phases support anyons, quasiparticles with exotic exchange statistics. The emergent nonlocal state spaces of anyonic systems admit a particular form of entanglement that does not exist in conventional quantum mechanical systems. We study this entanglement by adapting standard notions of entropy to anyonic systems. We use the algebraic theory of anyon models (modular tensor categories) to illustrate the nonlocal entanglement structure of anyonic systems. Using this formalism, we present a general method of deriving the universal topological contributions to the entanglement entropy for general system configurations of a topological phase, including surfaces of arbitrary genus, punctures, and quasiparticle content. We analyze a number of examples in detail. Our results recover and extend prior results for anyonic entanglement and the topological entanglement entropy.
An ALMA Dynamical Mass Estimate of the Proposed Planetary-mass Companion FW Tau C

Dynamical mass estimates down to the planet-mass regime can help to understand planet formation. We present Atacama Large Millimeter/submillimeter Array (ALMA) 1.3 mm observations of FW Tau C, a proposed ~10 M Jup planet-mass companion at ~330 au from the host binary FW Tau AB. We spatially and spectrally resolve the accretion disk of FW Tau C in 12CO (2–1). By modeling the Keplerian rotation of gas, we derive a dynamical mass of ~0.1 M ☉. Therefore, FW Tau C is unlikely a planet, but rather a low-mass star with a highly inclined disk. This also suggests that FW Tau is a triple system consisting of three ~0.1 M ☉ stars.
Constraining the Rotation Rate of Transiting Extrasolar Planets by Oblateness Measurements

The solar system gas giant planets are oblate due to their rapid rotation. A measurement of the planet's projected oblateness would constrain the planet's rotational period. Planets that are synchronously rotating with their orbital revolution will be rotating too slowly to be significantly oblate; these include planets with orbital semimajor axes 0.2 AU (for MP ~ MJupiter and M* ~ M☉). Jupiter-like planets in the range of orbital semimajor axis 0.1 to 0.2 AU will tidally evolve to synchronous rotation on a timescale similar to main-sequence stars' lifetimes. In this case, an oblateness detection will help constrain the planet's tidal Q value. The projected oblateness of a transiting extrasolar giant planet is measurable from a very high photometric precision transit light curve. For a Sun-sized star and a Jupiter-sized planet, the normalized flux difference in the transit ingress/egress light curve between a spherical and an oblate planet is a few to 15 × 10-5 for oblateness similar to Jupiter and Saturn, respectively. The transit ingress and egress are asymmetric for an oblate planet with orbital inclination different from 90° and a nonzero projected obliquity. A photometric precision of 10-4 has been reached by Hubble Space Telescope (HST) observations of the known transiting extrasolar planet HD 209458b. Kepler, a NASA discovery-class mission designed to detect transiting Earth-sized planets, requires a photometric precision of 10-5 and expects to find 30 to 40 transiting giant planets with orbital semimajor axes 0.2 AU. Furthermore, part-per-million photometric precision (reached after averaging over several orbital periods) is expected from three other space telescopes to be launched within the next three years. Thus, an oblateness measurement of a transiting giant planet is realistic in the near future.
(0, 2) Target-space duality, CICYs and reflexive sheaves

Abstract It is shown that the recently proposed target-space duality for (0, 2) models is not limited to models admitting a Landau-Ginzburg description. By studying some generic examples it is established for the broader class of vector bundles over complete intersections in toric varieties. Instead of sharing a common Landau-Ginzburg locus, a pair of dual models agrees in more general non-geometric phases. The mathematical tools for treating reflexive sheaves are provided as well.
The Least-Action Principle: Theory of Cosmological Solutions and the Radial Velocity Action

Formulating the equations of motion for cosmological bodies (such as galaxies) in an integral, rather than differential, form has several advantages. Using an integral, the mathematical instability at early times is avoided, and the boundary conditions of the integral correspond closely with available data. Here it is shown that such a least-action calculation for a number of bodies interacting through gravity has a finite number of solutions, possibly only one. Characteristics of the different possible solutions are explored. The results are extended to cover the motion of a continuous fluid. We give a method for generalizing an action so as to use velocities, instead of positions, in boundary conditions, which reduces in particular cases to those given by Giavalisco et al. and Schmoldt & Saha. The velocity boundary condition is shown to have no effect on the number of solutions.
Unitarity and the Holographic S-Matrix

The bulk S-Matrix can be given a non-perturbative definition in terms of the flat space limit of AdS/CFT. We show that the unitarity of the S-Matrix, ie the optical theorem, can be derived by studying the behavior of the OPE and the conformal block decomposition in the flat space limit. When applied to perturbation theory in AdS, this gives a holographic derivation of the cutting rules for Feynman diagrams. To demonstrate these facts we introduce some new techniques for the analysis of conformal field theories. Chief among these is a method for conglomerating local primary operators $ {{\mathcal{O}}_1} $ and $ {{\mathcal{O}}_2} $ to extract the contribution of an individual primary $ {{\mathcal{O}}_{{\varDelta, \ell }}} $ in their OPE. This provides a method for isolating the contribution of specific conformal blocks which we use to prove an important relation between certain conformal block coefficients and anomalous dimensions. These techniques make essential use of the simplifications that occur when CFT correlators are expressed in terms of a Mellin amplitude.
Elastohydrodynamics of swimming helices: Effects of flexibility and confinement

We examine the swimming of an elastic helix rotated by a torque at its base, both in free-space and confined to a tube. The image depicts the envelope of an excursion of a filament centerline over one rotation; the blue is the surface of the finite-radius helical filament at one snapshot in time.
Mass-Temperature Relation of Galaxy Clusters: A Theoretical Study

Combining conservation of energy throughout the nearly spherical collapse of galaxy clusters with the virial theorem, we derive the mass-temperature relation for X-ray clusters of galaxies, T = CM2/3. The normalization factor C and the scatter of the relation are determined from first principles, with the additional assumption of an initial Gaussian random field. We are also able to reproduce the recently observed break in the M-T relation at T ~ 3 keV, based on the scatter in the underlying density field for a low-density ΛCDM cosmology. Finally, by combining observational data of high-redshift clusters with our theoretical formalism, we find a semiempirical temperature-mass relation that is expected to hold at redshifts up to unity with less than 20% error.
Modeling, Analysis, and Mitigation of Dynamic Botnet Formation in Wireless IoT Networks

The Internet of Things (IoT) relies heavily on wireless communication devices that are able to discover and interact with other wireless devices in their vicinity. The communication flexibility coupled with software vulnerabilities in devices, due to low cost and short time-to-market, exposes them to a high risk of malware infiltration. Malware may infect a large number of network devices using device-to-device (D2D) communication resulting in the formation of a botnet, i.e., a network of infected devices controlled by a common malware. A botmaster may exploit it to launch a network-wide attack sabotaging infrastructure and facilities, or for malicious purposes such as collecting ransom. In this paper, we propose an analytical model to study the D2D propagation of malware in wireless IoT networks. Leveraging tools from dynamic population processes and point process theory, we capture malware infiltration and coordination process over a network topology. The analysis of mean-field equilibrium in the population is used to construct and solve an optimization problem for the network defender to prevent botnet formation by patching devices while causing minimum overhead to network operation. The developed analytical model serves as a basis for assisting the planning, design, and defense of such networks from a defender’s standpoint.
THE MASS AND RADIUS OF THE NEUTRON STAR IN THE BULGE LOW-MASS X-RAY BINARY KS 1731-260

Measurements of neutron star masses and radii are instrumental in determining the equation of state of their interiors, understanding the dividing line between neutron stars and black holes, and obtaining accurate statistics of source populations in the Galaxy. We report here on the measurement of the mass and radius of the neutron star in the low-mass X-ray binary KS 1731–260. The analysis of the spectroscopic data on multiple thermonuclear bursts yields well-constrained values for the apparent angular area and the Eddington flux of the source, both of which depend in a distinct way on the mass and radius of the neutron star. The binary KS 1731–260 is in the direction of the Galactic bulge, allowing a distance estimate based on the density of stars in that direction. Making use of the Han & Gould model, we determine the probability distribution over the distance to the source, which is approximately flat between 7 and 9 kpc. Combining these measurements, we place a strong upper bound on the radius of the neutron star, R ≤ 12.5 km, while confining its mass to M ≤ 2.1 M ☉.
Modeling Self-Assembly of Diblock Copolymer-Nanoparticle Composites

A cell dynamics method for domain separation of diblock copolymers (DBCPs) interacting with nanoparticles (NPs) whose diffusion coefficients depend on chain configuration is proposed for self-assembly of DBCP/NP composites. Increasing NP concentration slows down domain separation, but matching NP diffusion lengths and lamellar size of DBCPs reduces this effect. The model also explains features of different nanocomposites, such as morphological transitions induced by NPs, the coexistence of lamellar and hexagonal patterns in a single sample, and peaked NP density profiles across the parallel domains.