cssi/SciSciGPT-SciSciNet huggingface dataset:
Autonomous Parking of Vehicle Fleet in Tight Environments.

The problem of autonomous parking of vehicle fleets is addressed in this paper. We present a system-level modeling and control framework which allows investigating different vehicle parking strategies while taking into account path planning and collision avoidance. The proposed approach decouples the problem into a centralized parking spot allocation and path generation, and a decentralized collision avoidance control. This paper presents the hierarchical framework and algorithmic details. Extensive simulations are used to assess several allocation strategies in terms of total fleet parking time and queue length. In particular, we observe that when parking large vehicle fleets, a phenomenon similar to Braess's paradox occurs.
Transformer-based Context-aware Sarcasm Detection in Conversation Threads from Social Media.

We present a transformer-based sarcasm detection model that accounts for the context from the entire conversation thread for more robust predictions. Our model uses deep transformer layers to perform multi-head attentions among the target utterance and the relevant context in the thread. The context-aware models are evaluated on two datasets from social media, Twitter and Reddit, and show 3.1% and 7.0% improvements over their baselines. Our best models give the F1-scores of 79.0% and 75.0% for the Twitter and Reddit datasets respectively, becoming one of the highest performing systems among 36 participants in this shared task.
The Memory-Tightness of Authenticated Encryption

This paper initiates the study of the provable security of authenticated encryption (AE) in the memory-bounded setting. Recent works – Tessaro and Thiruvengadam (TCC ’18), Jaeger and Tessaro (EUROCRYPT ’19), and Dinur (EUROCRYPT ’20) – focus on confidentiality, and look at schemes for which trade-offs between the attacker’s memory and its data complexity are inherent. Here, we ask whether these results and techniques can be lifted to the full AE setting, which additionally asks for integrity.
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo.

We show that the gradient norm $\norm{\nabla f(x)}$ for $x \sim \exp(-f(x))$, where $f$ is strongly convex and smooth, concentrates tightly around its mean. This removes a barrier in the prior state-of-the-art analysis for the well-studied Metropolized Hamiltonian Monte Carlo (HMC) algorithm for sampling from a strongly logconcave distribution \cite{DwivediCWY18}. We correspondingly demonstrate that Metropolized HMC mixes in $\tOh{\kappa d}$ iterations\footnote{We use $\tilde{O}$ to hide logarithmic factors in problem parameters.}, improving upon the $\tilde{O}(\kappa^{1.5}\sqrt{d}+ \kappa d)$ runtime of \cite{DwivediCWY18, ChenDWY19} by a factor $(\kappa/d)^{1/2}$ when the condition number $\kappa$ is large. Our mixing time analysis introduces several techniques which to our knowledge have not appeared in the literature and may be of independent interest, including restrictions to a nonconvex set with good conductance behavior, and a new reduction technique for boosting a constant-accuracy total variation guarantee under weak warmness assumptions. This is the first mixing time result for logconcave distributions using only first-order function information which achieves linear dependence on $\kappa$; we also give evidence that this dependence is likely to be necessary for standard Metropolized first-order methods.
Can increasing years of schooling reduce type 2 diabetes (T2D)?: Evidence from a Mendelian randomization of T2D and 10 of its risk factors

A focus in recent decades has involved examining the potential causal impact of educational attainment (schooling years) on a variety of disease and life-expectancy outcomes. Numerous studies have broadly revealed a link suggesting that as years of formal schooling increase so too does health and wellbeing; however, it is unclear whether the associations are causal. Here we use Mendelian randomization, an instrumental variables technique, with a two-sample design, to probe whether more years of schooling are causally linked to type 2 diabetes (T2D) and 10 of its attendant risk factors. The results revealed a protective effect of more schooling years against T2D (odds ratio = 0.39; 95% confidence interval: 0.26, 0.58; P = 3.89 × 10–06), which in turn might be partly mediated by more years of schooling being protective against the following: having a father with T2D, being overweight, having higher blood pressure and higher levels of circulating triglycerides, and having lower levels of HDL cholesterol. More schooling years had no effect on risk for gestational diabetes or polycystic ovarian syndrome and was associated with a decreased likelihood of moderate physical activity. These findings imply that strategies to retain adults in higher education may help reduce the risk for a major source of metabolic morbidity and mortality.
UDP-glucose 6-dehydrogenase knockout impairs migration and decreases in vivo metastatic ability of breast cancer cells

Dysregulated metabolism is a hallmark of cancer that supports tumor growth and metastasis. One understudied aspect of cancer metabolism is altered nucleotide sugar biosynthesis, which drives aberrant cell surface glycosylation known to support various aspects of cancer cell behavior including migration and signaling. We examined clinical association of nucleotide sugar pathway gene expression and found that UGDH, encoding UDP-glucose 6-dehydrogenase which catalyzes production of UDP-glucuronate, is associated with worse breast cancer patient survival. Knocking out the mouse homolog Ugdh in highly-metastatic 6DT1 breast cancer cells impaired migration ability without affecting in vitro proliferation. Further, Ugdh-KO resulted in significantly decreased metastatic capacity in vivo when the cells were orthotopically injected in syngeneic mice. Our experiments show that UDP-glucuronate biosynthesis is critical for metastasis in a mouse model of breast cancer.
Bipartite tight spectral clustering (BiTSC) algorithm for identifying conserved gene co-clusters in two species.

Author(s): Sun, Yidan Eden; Zhou, Heather J; Li, Jingyi Jessica | Abstract: MotivationGene clustering is a widely used technique that has enabled computational prediction of unknown gene functions within a species. However, it remains a challenge to refine gene function prediction by leveraging evolutionarily conserved genes in another species. This challenge calls for a new computational algorithm to identify gene co-clusters in two species, so that genes in each co-cluster exhibit similar expression levels in each species and strong conservation between the species.ResultsHere, we develop the bipartite tight spectral clustering (BiTSC) algorithm, which identifies gene co-clusters in two species based on gene orthology information and gene expression data. BiTSC novelly implements a formulation that encodes gene orthology as a bipartite network and gene expression data as node covariates. This formulation allows BiTSC to adopt and combine the advantages of multiple unsupervised learning techniques: kernel enhancement, bipartite spectral clustering, consensus clustering, tight clustering and hierarchical clustering. As a result, BiTSC is a flexible and robust algorithm capable of identifying informative gene co-clusters without forcing all genes into co-clusters. Another advantage of BiTSC is that it does not rely on any distributional assumptions. Beyond cross-species gene co-clustering, BiTSC also has wide applications as a general algorithm for identifying tight node co-clusters in any bipartite network with node covariates. We demonstrate the accuracy and robustness of BiTSC through comprehensive simulation studies. In a real data example, we use BiTSC to identify conserved gene co-clusters of Drosophila melanogaster and Caenorhabditis elegans, and we perform a series of downstream analysis to both validate BiTSC and verify the biological significance of the identified co-clusters.Availability and implementationThe Python package BiTSC is open-access and available at https://github.com/edensunyidan/BiTSC.Supplementary informationSupplementary data are available at Bioinformatics online.
Keratins and Plakin family cytolinker proteins control the length of epithelial microridge protrusions

Cells adopt a wide array of irregular and bumpy shapes, which are scaffolded by an internal structure called the cytoskeleton. This network of filaments can deform the cell membrane the way tent poles frame a canvas. Cells contain three types of cytoskeleton elements (actin filaments, intermediate filaments, and microtubules), each with unique chemical and mechanical properties. One of the main roles of the cytoskeleton is to create protrusions, a range of structures that ‘stick out’ of a cell to allow movement and interactions with the environment. Both actin filaments and microtubules help form protrusions, but the role of intermediate filaments remains unclear. Microridges are a type of protrusion found on cells covered by mucus, for instance on the surface of the eye, inside the mouth, or on fish skin. These small bumps are organised on the membrane of a cell in fingerprint-like arrangements. Scientists know that actin networks are necessary for microridges to form; yet, many structures supported by actin filaments are not stable over time, suggesting that another component of the cytoskeleton might be lending support. Intermediate filaments are the strongest, most stable type of cytoskeleton element, and they can connect to actin filaments via linker proteins. However, research has yet to show that this kind of cooperation happens in any membrane protrusion. Here, Inaba et al. used high-resolution microscopy to monitor microridge development in the skin of live fish. In particular, they focused on a type of intermediate filaments known as keratin filaments. This revealed that, inside microridges, the keratin and actin networks form alongside each other, with linker proteins called Envoplakin and Periplakin connecting the two structures together. Genetic experiments revealed that Envoplakin and Periplakin must attach to actin for microridges to start forming. However, the two proteins bind to keratin for protrusions to grow. This work therefore highlights how intermediate filaments and linker proteins contribute to the formation of these structures. Many tissues must be covered in mucus to remain moist and healthy. As microridges likely contribute to mucus retention, the findings by Inaba et al. may help to better understand how disorders linked to problems in mucus emerge.
Mirror Descent Algorithms for Minimizing Interacting Free Energy

This note considers the problem of minimizing interacting free energy. Motivated by the mirror descent algorithm, for a given interacting free energy, we propose a descent dynamics with a novel metric that takes into consideration the reference measure and the interacting term. This metric naturally suggests a monotone reparameterization of the probability measure. By discretizing the reparameterized descent dynamics with the explicit Euler method, we arrive at a new mirror-descent-type algorithm for minimizing interacting free energy. Numerical results are included to demonstrate the efficiency of the proposed algorithms.
The Perfection Premium

This research documents a perfection premium in evaluative judgments wherein individuals disproportionately reward perfection on an attribute compared to near-perfect values on the same attribute. ...
Improving the understanding of jet grooming in perturbation theory

Jet grooming has emerged as a necessary and powerful tool in a precision jet physics program. In this paper, we present three results on jet grooming in perturbation theory, focusing on heavy jet mass in e+e− → hadrons collisions, groomed with the modified mass drop tagger. First, we calculate the analytic cross section at leading-order. Second, using the leading-order result and numerical results through next-to-next-to-leading order, we show that cusps in the distribution on the interior of phase space at leading-order are softened at higher orders. Finally, using analytic and numerical results, we show that terms that violate the assumptions of the factorization theorem for groomed jet mass are numerically much smaller than expected from power counting. These results provide important information regarding the convergence of perturbation theory for groomed jet observables and reliable estimates for residual uncertainties in a precision calculation.
Quantitative study of unsaturated transport of glycerol through aquaglyceroporin that has high affinity for glycerol.

The structures of several aquaglyceroporins have been resolved to atomic resolution showing two or more glycerols bound inside a channel and confirming a glycerol-facilitator's affinity for its substrate glycerol. However, the kinetics data of glycerol transport experiments all point to unsaturated transport that is characteristic of low substrate affinity in terms of the Michaelis–Menten kinetics. In this article, we present in silico–in vitro research focused on AQP3, one of the human aquaglyceroporins that is natively expressed in the abundantly available erythrocytes. We conducted 2.1 μs in silico simulations of AQP3 embedded in a model erythrocyte membrane with intracellular–extracellular asymmetries in leaflet lipid compositions and compartment salt ions. From the equilibrium molecular dynamics (MD) simulations, we elucidated the mechanism of glycerol transport at high substrate concentrations. From the steered MD simulations, we computed the Gibbs free-energy profile throughout the AQP3 channel. From the free-energy profile, we quantified the kinetics of glycerol transport that is unsaturated due to glycerol–glycerol interactions mediated by AQP3 resulting in the concerted movement of two glycerol molecules for the transport of one glycerol molecule across the cell membrane. We conducted in vitro experiments on glycerol uptake into human erythrocytes for a wide range of substrate concentrations and various temperatures. The experimental data quantitatively validated our theoretical–computational conclusions on the unsaturated glycerol transport through AQP3 that has high affinity for glycerol.
Streamline-based simulation of nanoparticle transport in field-scale heterogeneous subsurface systems

Abstract Nanoparticle (NP) transport is increasingly relevant to subsurface engineering applications such as aquifer characterization and enhanced oil recovery. An efficient field-scale simulation framework is critical for predicting NP performance and designing subsurface applications. In this work, for the first time, a streamline-based model is presented to simulate NP transport in field-scale subsurface systems with heterogeneous permeability. It considers a series of smart behaviors exhibited by engineered nanoparticles (NPs), including time-triggered encapsulation, retention, formation damage effects and variable nanofluid viscosity. The key methods employed by the algorithm are streamline-based simulation (SLS) and an operator-splitting (OS) technique for modeling NP transport. The model is implemented in an in-house streamline-based code, which is verified against analytical solutions, commercial simulator and academic codes. Simulations on a synthetic three-dimensional (3D) nanocapsule application engineering design case, are also performed to investigate the effect of fluid and NP properties on the displacement pattern of an existing subsurface fluid.
Solving Stochastic Inverse Problems for Property–Structure Linkages Using Data-Consistent Inversion and Machine Learning

Determining process–structure–property linkages is one of the key objectives in material science, and uncertainty quantification plays a critical role in understanding both process–structure and structure–property linkages. In this work, we seek to learn a distribution of microstructure parameters that are consistent in the sense that the forward propagation of this distribution through a crystal plasticity finite element model matches a target distribution on materials properties. This stochastic inversion formulation infers a distribution of acceptable/consistent microstructures, as opposed to a deterministic solution, which expands the range of feasible designs in a probabilistic manner. To solve this stochastic inverse problem, we employ a recently developed uncertainty quantification framework based on push-forward probability measures, which combines techniques from measure theory and Bayes’ rule to define a unique and numerically stable solution. This approach requires making an initial prediction using an initial guess for the distribution on model inputs and solving a stochastic forward problem. To reduce the computational burden in solving both stochastic forward and stochastic inverse problems, we combine this approach with a machine learning Bayesian regression model based on Gaussian processes and demonstrate the proposed methodology on two representative case studies in structure–property linkages.
Data-Driven Hierarchical Predictive Learning in Unknown Environments

We propose a hierarchical learning architecture for predictive control in unknown environments. We consider a constrained nonlinear dynamical system and assume the availability of state-input trajectories solving control tasks in different environments. A parameterized environment model generates state constraints specific to each task, which are satisfied by the stored trajectories. Our goal is to find a feasible trajectory for a new task in an unknown environment. From stored data, we learn strategies in the form of target sets in a reduced-order state space. These strategies are applied to the new task in real-time using a local forecast of the new environment, and the resulting output is used as a terminal region by a low-level receding horizon controller. We show how to i) design the target sets from past data and then ii) incorporate them into a model predictive control scheme with shifting horizon that ensures safety of the closed-loop system when performing the new task. We prove the feasibility of the resulting control policy, and verify the proposed method in a robotic path planning application.
A model of discrete choice based on reinforcement learning under short-term memory

Abstract A family of models of individual discrete choice are constructed by means of statistical averaging of choices made by a subject in a reinforcement learning process, where the subject has a short, k-term memory span. The choice probabilities in these models combine in a non-trivial, non-linear way the initial learning bias and the experience gained through learning. The properties of such models are discussed and, in particular, it is shown that probabilities deviate from Luce’s Choice Axiom. Moreover, it is shown that the latter property is recovered as the memory span increases. Two different applications in utility theory are considered. In the first, we use the discrete choice model to generate a binary preference (weak stochastic order) relation on simple lotteries. We show that the relation violate the transitivity and independence axioms of expected utility theory. Furthermore, we establish the dependence of the preferences on frames, with risk aversion for gains, and risk seeking for losses. Based on these findings, we consider a parametric model of choice based on the probability maximization principle, as a model for deviations from the expected utility principle. To illustrate the approach, we apply this model to the classical problem of demand for insurance.
Stock price reactivity to earnings announcements: the role of the Cammer/Krogman factors

The stock characteristics often used in securities litigation to assess market efficiency are dispositive indicators of reactivity to earnings announcements. Stocks with large capitalization, high trading volume, broad analyst coverage, a large number of market makers, and narrow bid-ask spread are far more likely to react significantly to earnings announcements than stocks without these characteristics. Univariate and multivariate tests compel this conclusion, but provide weaker evidence for analyst coverage.
Rational curves on general type hypersurfaces

We develop a technique that allows us to prove results about subvarieties of general type hypersurfaces. As an application, we use a result of Clemens and Ran to prove that a very general hypersurface of degree $\frac{3n+1}{2} \leq d \leq 2n - 3$ in $\mathbb{P}^n$ contain lines but no other rational curves.
A uropathogenic E. coli UTI89 model of prostatic inflammation and collagen accumulation for use in studying aberrant collagen production in the prostate

Bacterial infection is one known etiology of prostatic inflammation. Prostatic inflammation is associated with prostatic collagen accumulation and both are linked to progressive lower urinary tract symptoms in men. We characterized a model of prostatic inflammation using transurethral instillations of Escherichia coli UTI89 in C57BL/6J male mice with the goal of determining the optimal instillation conditions, understanding the impact of instillation conditions on urinary physiology, and identifying ideal prostatic lobes and collagen 1a1 prostatic cell types for further analysis. The smallest instillation volume tested (50 µL) distributed exclusively to the bladder, 100- and 200-µL volumes distributed to the bladder and prostate, and a 500-µL volume distributed to the bladder, prostate, and ureter. A threshold optical density of 0.4 E. coli UTI89 in the instillation fluid was necessary for significant (P < 0.05) prostate colonization. E. coli UTI89 infection resulted in a low frequency, high volume spontaneous voiding pattern. This phenotype was due to exposure to E. coli UTI89, not catheterization alone, and was minimally altered by a 50-µL increase in instillation volume and doubling of E. coli concentration. Prostate inflammation was isolated to the dorsal prostate and was accompanied by increased collagen density. This was partnered with increased density of protein tyrosine phosphatase receptor type C+, procollagen type I-α1+ copositive cells and decreased density of α2-smooth muscle actin+, procollagen type I-α1+ copositive cells. Overall, we determined that this model is effective in altering urinary phenotype and producing prostatic inflammation and collagen accumulation in mice.
Inequality for Burkholder's martingale transform

We find the sharp constant $C=C(\tau,p, \mathbb{E}G, \mathbb{E}F)$ of the following inequality $\|(G^{2}+ \tau^{2} F^{2})^{1/2} \|_{p} \leq C \|F\|_{p},$ where $G$ is the transform of a martingale $F$ under a predictable sequence $\varepsilon$ with absolute value 1, $1<p< 2$, and $\tau$ is any real number.
Bit threads in higher-curvature gravity

We generalize holographic bit threads to bulk theories with a gravitational action containing higher-curvature terms. Bit threads are a reformulation of holographic entanglement entropy, where the entropy is given by the maximum number of threads emanating from a boundary region into the bulk. We show that the addition of higher-curvature terms adds corrections to the bit thread thickness that depend on the local geometry and thread orientation. Two different methods are given: determination of the density bound by requiring the maximum number of threads through a given surface to reproduce the entanglement entropy functional on that surface, and application of Lagrange dualization. The results of the two methods are applied to Gauss-Bonnet gravity as the simplest non-trivial example.
Detecting essential surfaces as intersections in the character variety

We describe a family of hyperbolic knots whose character variety contain exactly two distinct components of characters of irreducible representations. The intersection points between the components carry rich topological information. In particular, these points are nonintegral and detect a Seifert surface.
Supersymmetry and Wrapped Branes in Microstate Geometries

We consider the supergravity back-reaction of M2 branes wrapping around the space-time cycles in $$ \frac{1}{8} $$ -BPS microstate geometries. We show that such brane wrappings will generically break all the supersymmetries. In particular, all the supersymmetries will be broken if there are such wrapped branes but the net charge of the wrapped branes is zero. We show that if M2 branes wrap a single cycle, or if they wrap a several of co-linear cycles with the same orientation, then the solution will be $$ \frac{1}{16} $$ -BPS, having two supersymmetries. We comment on how these results relate to using W-branes to understand the microstate structure of $$ \frac{1}{8} $$ -BPS black holes.
PT-symmetric eigenvalues for homogeneous potentials

We consider one-dimensional Schrodinger equations with potential x2M(ix)e, where M ≥ 1 is an integer and e is real, under appropriate parity and time (PT)-symmetric boundary conditions. We prove the phenomenon which was discovered by Bender and Boettcher by numerical computation: as e changes, the real spectrum suddenly becomes non-real in the sense that all but finitely many eigenvalues become non-real. We find the limit arguments of these non-real eigenvalues E as E → ∞.
An analysis of the evolution of science-technology linkage in biomedicine

Abstract Demonstrating the practical value of public research has been an important subject in science policy. Here we present a detailed study on the evolution of the citation linkage between life science related patents and biomedical research over a 37-year period. Our analysis relies on a newly-created dataset that systematically links millions of non-patent references to biomedical papers. We find a large disparity in the volume of citations to science among technology sectors, with biotechnology and drug patents dominating it. The linkage has been growing exponentially over a long period of time, doubling every 2.9 years. The U.S. has been the largest producer of cited science for years, receiving nearly half of the citations. More than half of citations goes to universities. We use a new paper-level indicator to quantify to what extent a paper is basic research or clinical medicine. We find that the cited papers are likely to be basic research, yet a significant portion of papers cited in patents that are related to FDA-approved drugs are clinical research. The U.S. National Institute of Health continues to be an important funder of cited science. For the majority of companies, more than half of citations in their patents are authored by public research. Taken together, these results indicate a continuous linkage of public science to private sector inventions.
Switching of biaxial synthetic antiferromagnets: A micromagentic study

We simulate the switching behavior of nanoscale synthetic antiferromagnets (SAFs), inspired by recent experimental progress in spin-orbit-torque switching of crystal antiferromagnets. The SAF consists of two ferromagnetic thin films with in-plane biaxial anisotropy and interlayer exchange coupling. Staggered field-like Rashba spin-orbit torques from the opposite surfaces of the SAF induce a canted net magnetization, which triggers an orthogonal torque that drives 90 ° switching of the Neel vector. Such dynamics driven by the field-like spin-orbit torque allows for faster switching with increased Gilbert damping, without a significant detrimental increase of the threshold switching current density. Our results point to the potential of SAFs as model systems, based on simple ferromagnetic metals, to mimic antiferromagnetic device physics.We simulate the switching behavior of nanoscale synthetic antiferromagnets (SAFs), inspired by recent experimental progress in spin-orbit-torque switching of crystal antiferromagnets. The SAF consists of two ferromagnetic thin films with in-plane biaxial anisotropy and interlayer exchange coupling. Staggered field-like Rashba spin-orbit torques from the opposite surfaces of the SAF induce a canted net magnetization, which triggers an orthogonal torque that drives 90 ° switching of the Neel vector. Such dynamics driven by the field-like spin-orbit torque allows for faster switching with increased Gilbert damping, without a significant detrimental increase of the threshold switching current density. Our results point to the potential of SAFs as model systems, based on simple ferromagnetic metals, to mimic antiferromagnetic device physics.
A Computationally Efficient Multiclass Time-Frequency Common Spatial Pattern Analysis on EEG Motor Imagery

Common spatial pattern (CSP) is a popular feature extraction method for electroencephalogram (EEG) motor imagery (MI). This study modifies the conventional CSP algorithm to improve the multi-class MI classification accuracy and ensure the computation process is efficient. The EEG MI data is gathered from the Brain-Computer Interface (BCI) Competition IV. At first, a bandpass filter and a timefrequency analysis are performed for each experiment trial. Then, the optimal EEG signals for every experiment trials are selected based on the signal energy for CSP feature extraction. In the end, the extracted features are classified by three classifiers, linear discriminant analysis (LDA), naive Bayes (NVB), and support vector machine (SVM), in parallel for classification accuracy comparison.The experiment results show the proposed algorithm average computation time is 37.22% less than the FBCSP (1st winner in the BCI Competition IV) and 4.98% longer than the conventional CSP method. For the classification rate, the proposed algorithm kappa value achieved 2nd highest compared with the top 3 winners in BCI Competition IV.
On the missing log in upper tail estimates

Abstract In the late 1990s, Kim and Vu pioneered an inductive method for showing concentration of certain random variables X. Shortly afterwards, Janson and Rucinski developed an alternative inductive approach, which often gives comparable results for the upper tail P ( X ≥ ( 1 + e ) E X ) . In some cases, both methods yield upper tail estimates which are best possible up to a logarithmic factor in the exponent, but closing this narrow gap has remained a technical challenge. In this paper we present a BK-inequality based combinatorial sparsification idea that can recover this missing logarithmic term in the upper tail. As an illustration, we consider random subsets of the integers { 1 , … , n } , and prove sharp upper tail estimates for various objects of interest in additive combinatorics. Examples include the number of arithmetic progressions, Schur triples, additive quadruples, and ( r , s ) -sums.
Exploiting Locality in Quantum Computation for Quantum Chemistry.

Accurate prediction of chemical and material properties from first-principles quantum chemistry is a challenging task on traditional computers. Recent developments in quantum computation offer a route toward highly accurate solutions with polynomial cost; however, this solution still carries a large overhead. In this Perspective, we aim to bring together known results about the locality of physical interactions from quantum chemistry with ideas from quantum computation. We show that the utilization of spatial locality combined with the Bravyi–Kitaev transformation offers an improvement in the scaling of known quantum algorithms for quantum chemistry and provides numerical examples to help illustrate this point. We combine these developments to improve the outlook for the future of quantum chemistry on quantum computers.
Gonality of dynatomic curves and strong uniform boundedness of preperiodic points

Fix and a field such that . Assume that contains the th roots of . Then the irreducible components of the curves over parameterizing preperiodic points of polynomials of the form are geometrically irreducible and have gonality tending to . This implies the function field analogue of the strong uniform boundedness conjecture for preperiodic points of . It also has consequences over number fields: it implies strong uniform boundedness for preperiodic points of bounded eventual period, which in turn reduces the full conjecture for preperiodic points to the conjecture for periodic points. Our proofs involve a novel argument specific to finite fields, in addition to more standard tools such as the Castelnuovo–Severi inequality.
A rank inequality for the annular Khovanov homology of 2–periodic links

For a 2 –periodic link L in the thickened annulus and its quotient link L , we exhibit a spectral sequence with E 1 ≅ AKh ( L ) ⊗ F F [ θ , θ − 1 ] ⇉ E ∞ ≅ AKh ( L ) ⊗ F F [ θ , θ − 1 ] . This spectral sequence splits along quantum and s l 2 weight-space gradings, proving a rank inequality rk AKh j , k ( L ) ≤ rk AKh 2 j − k , k ( L ) for every pair of quantum and s l 2 weight-space gradings ( j , k ) . We also present a few decategorified consequences and discuss partial results toward a similar statement for the Khovanov homology of 2 –periodic links, as well as some frameworks for obstructing 2 –periodicity in links.
Cross-Correlation of Near and Far-Infrared Background Anisotropies as Traced by Spitzer and Herschel

We present the cross-correlation between the far-infrared background fluctuations as measured with the Herschel Space Observatory at 250, 350, and 500 μm and the near-infrared background fluctuations with Spitzer Space Telescope at 3.6 μm. The cross-correlation between far and near-IR background anisotropies are detected such that the correlation coefficient at a few to ten arcminute angular scales decreases from 0.3 to 0.1 when the far-IR wavelength increases from 250 μm to 500 μm. We model the cross-correlation using a halo model with three components: (a) far-IR bright or dusty starforming galaxies below the masking depth in Herschel maps, (b) near-IR faint galaxies below the masking depth at 3.6 μm, and (c) intra-halo light, or diffuse stars in dark matter halos, that is likely dominating fluctuations at 3.6 μm. The model is able to reasonably reproduce the auto correlations at each of the far-IR wavelengths and at 3.6 μm and their corresponding cross-correlations. While the far and near-IR auto-correlations are dominated by faint dusty, starforming galaxies and intra-halo light, respectively, we find that roughly half of the cross-correlation between near and far-IR backgrounds is due to the same dusty galaxies that remain unmasked at 3.6 μm. The remaining signal in the cross-correlation is due to intra-halo light present in the same dark matter halos as those hosting the same faint and unmasked galaxies. In this model the decrease in the cross-correlation signal from 250 μm to 500 μm comes from the fact that the galaxies that are primarily contributing to 500 μm fluctuations peak at a higher redshift than those at 250 μm. Subject headings: cosmology: observations – submillimeter: galaxies – infrared: galaxies – galaxies: evolution – cosmology: large-scale structure of Universe
Pulsar Timing at the Deep Space Network

The 70-m DSN’s Deep Space Station antenna 14 (DSS-14) at Goldstone has recently been outfitted with instrumentation to enable pulsar searching and timing operation. Systems capable of similar operations are undergoing installation at DSS-63, and are planned for DSS-43. The Goldstone system is the first of these to become operational with a 640MHz bandwidth stretching from 1325–1965MHz. Initial results from the pulsar timing pipeline show short-term residuals of <100ns for pulsar B1937+21. Commissioning observations at DSS-14 to obtain a baseline set of time of arrival (TOA) measurements on several millisecond pulsars (MSPs) are currently underway.
Self-similarity and universality in Rayleigh–Taylor, Boussinesq turbulence

We report and discuss case study simulations of the Rayleigh–Taylor instability in the Boussinesq, incompressible regime developed to turbulence. Our main focus is on a statistical analysis of density and velocity fluctuations inside of the already developed and growing in size mixing zone. Novel observations reported in the article concern self-similarity of the velocity and density fluctuations spectra inside of the mixing zone snapshot, independence of the spectra of the horizontal slice level, and universality showing itself in a virtual independence of the internal structure of the mixing zone, measured in the rescaled spatial units, of the initial interface perturbations.
Index characterization for free boundary minimal surfaces

In this paper, we compute the Morse index for a free boundary minimal submanifold from data of two simpler problems. The first one is the corresponding problem with fixed boundary condition; and the second is associated with the Dirichlet-to-Neumann map for Jacobi fields. As an application, we show that the Morse index of a free boundary minimal annulus is equal to 4 if and only if it is the critical catenoid.
A Simple Proof of Perelman’s Collapsing Theorem for 3-manifolds

We will simplify earlier proofs of Perelman’s collapsing theorem for 3-manifolds given by Shioya–Yamaguchi (J. Differ. Geom. 56:1–66, 2000; Math. Ann. 333: 131–155, 2005) and Morgan–Tian (arXiv:0809.4040v1 [math.DG], 2008). A version of Perelman’s collapsing theorem states: “Let\(\{M^{3}_{i}\}\)be a sequence of compact Riemannian 3-manifolds with curvature bounded from below by (−1) and\(\mathrm{diam}(M^{3}_{i})\ge c_{0}>0\). Suppose that all unit metric balls in\(M^{3}_{i}\)have very small volume, at mostvi→0 asi→∞, and suppose that either\(M^{3}_{i}\)is closed or has possibly convex incompressible toral boundary. Then\(M^{3}_{i}\)must be a graph manifold for sufficiently largei”. This result can be viewed as an extension of the implicit function theorem. Among other things, we apply Perelman’s critical point theory (i.e., multiple conic singularity theory and his fibration theory) to Alexandrov spaces to construct the desired local Seifert fibration structure on collapsed 3-manifolds.
On the Asymptotic Stability of Steady Flows with Nonzero Flux in Two-Dimensional Exterior Domains

The Navier–Stokes equations in a two-dimensional exterior domain are considered. The asymptotic stability of stationary solutions satisfying a general hypothesis is proven under any L2-perturbation. In particular, the general hypothesis is valid if the steady solution is the sum of the critically decaying flux carrier with flux \({\left| \Phi \right| < 2 \pi}\) and a small subcritically decaying term. Under the central symmetry assumption, the general hypothesis is also proven for any critically decaying steady solutions under a suitable smallness condition.
Brane interaction as the origin of inflation

We reanalyze brane inflation with brane-brane interactions at an angle, which include the special case of brane-anti-brane interaction. If nature is described by a stringy realization of the brane world scenario today (with arbitrary compactification), and if some additional branes were present in the early universe, we find that an inflationary epoch is generically quite natural, ending with a big bang when the last branes collide. In an interesting brane inflationary scenario suggested by generic string model-building, we use the density perturbation observed in the cosmic microwave background and the coupling unification to find that the string scale is comparable to the GUT scale.
Soft parton radiation in polarized vector boson production: theoretical issues

Abstract Accurate measurement of spin-dependent parton distributions in production of electroweak bosons with polarized proton beams at the Relativistic Heavy Ion Collider depends on good understanding of QCD radiation at small transverse momenta qT of vector bosons. We present a theoretical formalism for small-qT resummation of the cross sections for production of γ ∗ , W±, and Z0 bosons, with the subsequent decay of these bosons into lepton pairs, for arbitrary longitudinal polarizations of the proton beams.
Bertini irreducibility theorems over finite fields

Given a geometrically irreducible subscheme X in P^n over F_q of dimension at least 2, we prove that the fraction of degree d hypersurfaces H such that the intersection of H and X is geometrically irreducible tends to 1 as d tends to infinity. We also prove variants in which X is over an extension of F_q, and in which the immersion of X in P^n is replaced by a more general morphism.
Exact heat kernel on a hypersphere and its applications in kernel SVM

Many contemporary statistical learning methods assume a Euclidean feature space. This paper presents a method for defining similarity based on hyperspherical geometry and shows that it often improves the performance of support vector machine compared to other competing similarity measures. Specifically, the idea of using heat diffusion on a hypersphere to measure similarity has been previously proposed and tested by \citet{Lafferty:2015uy}, demonstrating promising results based on a heuristic heat kernel obtained from the zeroth order parametrix expansion; however, how well this heuristic kernel agrees with the exact hyperspherical heat kernel remains unknown. This paper presents a higher order parametrix expansion of the heat kernel on a unit hypersphere and discusses several problems associated with this expansion method. We then compare the heuristic kernel with an exact form of the heat kernel expressed in terms of a uniformly and absolutely convergent series in high-dimensional angular momentum eigenmodes. Being a natural measure of similarity between sample points dwelling on a hypersphere, the exact kernel often shows superior performance in kernel SVM classifications applied to text mining, tumor somatic mutation imputation, and stock market analysis.
RADIATION-HYDRODYNAMIC SIMULATIONS OF MASSIVE STAR FORMATION WITH PROTOSTELLAR OUTFLOWS

We report the results of a series of adaptive mesh refinement radiation-hydrodynamic simulations of the collapse of massive star-forming clouds using the ORION code. These simulations are the first to include the feedback effects protostellar outflows, as well as protostellar radiative heating and radiation pressure exerted on the infalling, dusty gas. We find that outflows evacuate polar cavities of reduced optical depth through the ambient core. These enhance the radiative flux in the poleward direction so that it is 1.7-15 times larger than that in the midplane. As a result the radiative heating and outward radiation force exerted on the protostellar disk and infalling cloud gas in the equatorial direction are greatly diminished. This simultaneously reduces the Eddington radiation pressure barrier to high-mass star formation and increases the minimum threshold surface density for radiative heating to suppress fragmentation compared to models that do not include outflows. The strength of both these effects depends on the initial core surface density. Lower surface density cores have longer free-fall times and thus massive stars formed within them undergo more Kelvin contraction as the core collapses, leading to more powerful outflows. Furthermore, in lower surface density clouds the ratio of the time required for the outflow to break out of the core to the core free-fall time is smaller, so that these clouds are consequently influenced by outflows at earlier stages of the collapse. As a result, outflow effects are strongest in low surface density cores and weakest in high surface density ones. We also find that radiation focusing in the direction of outflow cavities is sufficient to prevent the formation of radiation pressure-supported circumstellar gas bubbles, in contrast to models which neglect protostellar outflow feedback.
The Burau representation is not faithful for n = 5

The Burau representation is a natural action of the braid group Bn on the free ℤ[t,t−1]–module of rank n−1. It is a longstanding open problem to determine for which values of n this representation is faithful. It is known to be faithful for n=3. Moody has shown that it is not faithful for n≥9 and Long and Paton improved on Moody’s techniques to bring this down to n≥6. Their construction uses a simple closed curve on the 6–punctured disc with certain homological properties. In this paper we give such a curve on the 5–punctured disc, thus proving that the Burau representation is not faithful for n≥5.
Transform Methods for Heavy-Traffic Analysis

The drift method was recently developed to study queuing systems in steady state. It was used successfully to obtain bounds on the moments of the scaled queue lengths that are asymptotically tight ...
Molecules at High Redshift: The Evolution of the Cool Phase of Protogalactic Disks

We study the formation of molecular hydrogen, after the epoch of reionization, in the context of canonical galaxy formation theory due to hierarchical clustering. There is an initial epoch of H2 production in the gas phase through the H- route that ends at a redshift of order unity. We assume that the fundamental units in the gas phase of protogalaxies during this epoch are similar to diffuse clouds found in our own Galaxy, and we restrict our attention to protogalactic disks, although some of our analysis applies to multiphase halo gas. Giant molecular clouds are not formed until lower redshifts. Star formation in the protogalactic disks can become self-regulated. The process responsible for the feedback is the heating of the gas by the internal stellar radiation field that can dominate the background radiation field at various epochs. If the gas is heated to above 2000-3000 K, the hydrogen molecules are collisionally dissociated, and we assume that in their absence the star formation process is strongly suppressed because of insufficient cooling. As we demonstrate by the analysis of phase diagrams, the H2-induced cool phase disappears. A priori, the cool phase with molecular hydrogen cooling can only achieve temperatures ≥300 K. Consequently, it is possible to define a maximum star formation rate during this epoch. Plausible estimates give a rate of 0.2-2 M☉ yr-1 for condensations corresponding to 1 σ and 2 σ initial density fluctuations. For more massive structures, this limit is relaxed and in agreement with observations of high-redshift galaxies. Therefore, the production of metals and dust proceeds slowly in this phase. This moderate epoch is terminated by a phase transition to a cold, dense, and warm neutral/ionized medium once the metals and dust have increased to a level Z ≈ 0.03-0.1 Z☉. Then (1) atoms and molecules such as C, O, and CO become abundant and cool the gas to below 300 K; (2) the dust abundance has become sufficiently high to allow shielding of the molecular gas; and (3) molecular hydrogen formation can occur rapidly on grain surfaces. This phase transition occurs at a redshift of approximately 1.5, with a fiducial range of 1.2 ≤ z ≤ 2, and initiates the rapid formation of molecular species, giant molecular clouds, and stars. Consequently, the delayed initiation of the cold phase in the interstellar medium of protostellar disks at a metallicity of Z 0.1 Z☉ is a plausible physical reason why the formation phase of the stellar disks of the bulk of the galaxies occurs only at a redshift of order unity. The combination of feedback and a phase transition provides a natural resolution of the G-dwarf problem.
An Improved Parametrized Representation of the Secondary He Neutral Flow in its Source Region

Analysis of data from the Interstellar Boundary EXplorer (IBEX) has revealed the presence of a flow of neutral helium through the inner solar system that most likely emanates from the outer heliosheath, where a distinct population of neutral He is produced by charge exchange processes. This secondary He flow has been modeled using codes designed to study interstellar flows through the heliosphere, but a laminar flow is not a good approximation for the outer heliosheath. I present a simple parametrization for a more appropriate divergent flow, and demonstrate how the secondary He particles might provide a means to remotely measure the divergence of the ISM flow around the heliopause.