cssi/SciSciGPT-SciSciNet huggingface dataset:
deBInfer: Bayesian inference for dynamical models of biological systems in R

Summary Understanding the mechanisms underlying biological systems, and ultimately, predicting their behaviours in a changing environment, requires overcoming the gap between mathematical models and experimental or observational data. Differential equations (DEs) are commonly used to model the temporal evolution of biological systems, but statistical methods for comparing DE models to data and for parameter inference are relatively poorly developed. This is especially problematic in the context of biological systems where observations are often noisy and only a small number of time points may be available. The Bayesian approach offers a coherent framework for parameter inference that can account for multiple sources of uncertainty, while making use of prior information. It offers a rigorous methodology for parameter inference, as well as modelling the link between unobservable model states and parameters, and observable quantities. We present deBInfer, a package for the statistical computing environment R, implementing a Bayesian framework for parameter inference in DEs. deBInfer provides templates for the DE model, the observation model and data likelihood, and the model parameters and their prior distributions. A Markov chain Monte Carlo (MCMC) procedure processes these inputs to estimate the posterior distributions of the parameters and any derived quantities, including the model trajectories. Further functionality is provided to facilitate MCMC diagnostics, the visualization of the posterior distributions of model parameters and trajectories, and the use of compiled DE models for improved computational performance. The templating approach makes deBInfer applicable to a wide range of DE models. We demonstrate its application to ordinary and delay DE models for population ecology.
A density tensor hierarchy for open system dynamics: retrieving the noise

We develop a density tensor hierarchy for open system dynamics that recovers information about fluctuations (or 'noise') lost in passing to the reduced density matrix. For the case of fluctuations arising from a classical probability distribution, the hierarchy is formed from expectations of products of pure state density matrix elements and can be compactly summarized by a simple generating function. For the case of quantum fluctuations arising when a quantum system interacts with a quantum environment in an overall pure state, the corresponding hierarchy is defined as the environmental trace of products of system matrix elements of the full density matrix. Whereas all members of the classical noise hierarchy are system observables, only the lowest member of the quantum noise hierarchy is directly experimentally measurable. The unit trace and idempotence properties of the pure state density matrix imply descent relations for the tensor hierarchies, that relate the order n tensor, under contraction of appropriate pairs of tensor indices, to the order n − 1 tensor. As examples to illustrate the classical probability distribution formalism, we consider a spatially isotropic ensemble of spin-1/2 pure states, a quantum system evolving by an Ito stochastic Schrodinger equation and a quantum system evolving by a jump process Schrodinger equation. As examples to illustrate the corresponding trace formalism in the quantum fluctuation case, we consider the tensor hierarchies for collisional Brownian motion of an infinite mass Brownian particle and for the weak coupling Born–Markov master equation. In different specializations, the latter gives the hierarchies generalizing the quantum optical master equation and the Caldeira–Leggett master equation. As a further application of the density tensor, we contrast stochastic Schrodinger equations that reduce and that do not reduce the state vector, and discuss why a quantum system coupled to a quantum environment behaves like the latter. The descent relations for our various examples are checked in a series of appendices.
Coherence and decoherence in tunneling between quantum dots

Coupled quantum dots are an example of the ubiquitous quantum double potential well. In a typical transport experiment, each quantum dot is also coupled to a continuum of states. Our approach takes this into account by using a Green's function formalism to solve the full system. The time-dependent solution is then explored in different limiting cases. In general, a combination of coherent and incoherent behavior is observed. In the case that the coupling of each dot to the macroscopic world is equal, however, the time evolution is purely coherent.
Quantum simulation from the bottom up: the case of rebits

Typically, quantum mechanics is thought of as a linear theory with unitary evolution governed by the Schrodinger equation. While this is technically true and useful for a physicist, with regards to computation it is an unfortunately narrow point of view. Just as a classical computer can simulate highly nonlinear functions of classical states, so too can the more general quantum computer simulate nonlinear evolutions of quantum states. We detail one particular simulation of nonlinearity on a quantum computer, showing how the entire class of $\mathbb{R}$-unitary evolutions (on $n$ qubits) can be simulated using a unitary, real-amplitude quantum computer (consisting of $n+1$ qubits in total). These operators can be represented as the sum of a linear and antilinear operator, and add an intriguing new set of nonlinear quantum gates to the toolbox of the quantum algorithm designer. Furthermore, a subgroup of these nonlinear evolutions, called the $\mathbb{R}$-Cliffords, can be efficiently classically simulated, by making use of the fact that Clifford operators can simulate non-Clifford (in fact, non-linear) operators. This perspective of using the physical operators that we have to simulate non-physical ones that we do not is what we call bottom-up simulation, and we give some examples of its broader implications.
Multi-Task Pharmacovigilance Mining from Social Media Posts

Social media has grown to be a crucial information source for pharmacovigilance studies where an increasing number of people post adverse reactions to medical drugs that are previously unreported. Aiming to effectively monitor various aspects of Adverse Drug Reactions (ADRs) from diversely expressed social medical posts, we propose a multi-task neural network framework that learns several tasks associated with ADR monitoring with different levels of supervisions collectively. Besides being able to correctly classify ADR posts and accurately extract ADR mentions from online posts, the proposed framework is also able to further understand reasons for which the drug is being taken, known as »indications», from the given social media post. A coverage-based attention mechanism is adopted in our framework to help the model properly identify »phrasal» ADRs and Indications that are attentive to multiple words in a post. Our framework is applicable in situations where limited parallel data for different pharmacovigilance tasks are available. We evaluate the proposed framework on real-world Twitter datasets, where the proposed model outperforms the state-of-the-art alternatives of each individual task consistently.
Tracing the peculiar dark matter structure in the galaxy cluster Cl 0024+17 with intracluster stars and gas

Intracluster light (ICL) is believed to originate from the stars stripped from cluster galaxies. They are no longer gravitationally bound to individual galaxies, but to the cluster, and their smooth distribution potentially makes them serve as much denser tracers of the cluster dark matter than the sparsely distributed cluster galaxies. We present our study of the ICL in the galaxy cluster Cl 0024+17 using both Advanced Camera for Surveys (ACS) and Subaru data, where we previously reported the discovery of a ring-like dark matter structure with gravitational lensing. The ACS images provide much lower sky levels than ground-based data, and enable us to measure relative variation of surface brightness reliably. This analysis is repeated with the Subaru images to examine if consistent features are recovered despite a different reduction scheme and different instrumental characteristics. We find that the ICL profile clearly resembles the peculiar mass profile, which stops decreasing at r ~ 50'' (~265 kpc) and slowly increases until it turns over at r ~ 75'' (~397 kpc). This feature is seen in both ACS and Subaru images for nearly all available passband images while the features are in general stronger in red filters. The consistency across different filters and instruments strongly rules out the possibility that the feature might come from any residual, uncorrected calibration errors. In addition, our re-analysis of the cluster X-ray data shows that the peculiar mass structure is also indicated by a non-negligible (3.7? in Chandra and 2.4? in XMM-Newton) bump in the intracluster gas profile when the geometric center of the dark matter ring, not the peak of the X-ray emission, is chosen as the center of the radial bin. The location of the gas ring is closer to the center by ~15'' (~80 kpc), raising an interesting possibility that the ring-like structure is expanding and the gas ring is lagging behind perhaps because of the ram pressure if both features in mass and gas share the same dynamical origin.
Transferring multiscale map styles using generative adversarial networks

The advancement of the Artificial Intelligence (AI) technologies makes it possible to learn stylistic design criteria from existing maps or other visual art and transfer these styles to make new di...
OptShrink: An Algorithm for Improved Low-Rank Signal Matrix Denoising by Optimal, Data-Driven Singular Value Shrinkage

The truncated singular value decomposition of the measurement matrix is the optimal solution to the representation problem of how to best approximate a noisy measurement matrix using a low-rank matrix. Here, we consider the (unobservable) denoising problem of how to best approximate a low-rank signal matrix buried in noise by optimal (re)weighting of the singular vectors of the measurement matrix. We exploit recent results from random matrix theory to exactly characterize the large matrix limit of the optimal weighting coefficients and show that they can be computed directly from data for a large class of noise models that includes the independent identically distributed Gaussian noise case. Our analysis brings into sharp focus the shrinkage-and-thresholding form of the optimal weights, the nonconvex nature of the associated shrinkage function (on the singular values), and explains why matrix regularization via singular value thresholding with convex penalty functions (such as the nuclear norm) will always be suboptimal. We validate our theoretical predictions with numerical simulations, develop an implementable algorithm (OptShrink) that realizes the predicted performance gains and show how our methods can be used to improve estimation in the setting where the measured matrix has missing entries.
General purpose multiplexing device for cryogenic microwave systems

We introduce and experimentally characterize a general purpose device for signal processing in circuit quantum electrodynamics systems. The device is a broadband two-port microwave circuit element with three modes of operation: it can transmit, reflect, or invert incident signals between 4 and 8 GHz. This property makes it a versatile tool for lossless signal processing at cryogenic temperatures. In particular, rapid switching (≤ 15 ns) between these operation modes enables several multiplexing readout protocols for superconducting qubits. We report the device's performance in a two-channel code domain multiplexing demonstration. The multiplexed data are recovered with fast readout times (up to 400 ns) and infidelities ≤ 10−2 for probe powers ≥ 7 fW, in agreement with the expectation for binary signaling with Gaussian noise.
Protostellar Outflows in L1340

We have searched the L1340 A, B, and C clouds for shocks from protostellar outflows using the H_2 2.122 μm near-infrared line as a shock tracer. Substantial outflow activity has been found in each of the three regions of the cloud (L1340 A, L1340 B, and L1340 C). We find 42 distinct shock complexes (16 in L1340 A, 11 in L1340 B, and 15 in L1340 C). We were able to link 17 of those shock complexes into 12 distinct outflows and identify candidate source stars for each. We examine the properties (A_V, T_(bol), and L_(bol)) of the source protostars and compare them to the properties of the general population of Class 0/I and flat spectral energy distribution protostars and find that there is an indication, albeit at low statistical significance, that the outflow-driving protostars are drawn from a population with lower A_V, higher L_(bol), and lower T_(bol) than the general population of protostars.
The Propagation of Chaos for a Rarefied Gas of Hard Spheres in the Whole Space

We discuss old and new results on the mathematical justification of Boltzmann’s equation. The classical result along these lines is a theorem which was proven by Lanford in the 1970s. This paper is naturally divided into three parts. I. Classical. We give new proofs of both the uniform bounds required for Lanford’s theorem, as well as the related bounds due to Illner and Pulvirenti for a perturbation of vacuum. The proofs use a duality argument and differential inequalities, instead of a fixed point iteration. II. Strong chaos. We introduce a new notion of propagation of chaos. Our notion of chaos provides for uniform error estimates on a very precise set of points; this set is closely related to the notion of strong (one-sided) chaos and the emergence of irreversibility. III. Supplemental. We announce and provide a proof (in “Appendix A”) of the propagation of partial factorization at some phase-points where complete factorization is impossible.
TeamPhone: Networking SmartPhones for Disaster Recovery

In this paper, we investigate how to network smartphones for providing communications in disaster recovery. By bridging the gaps among different kinds of wireless networks, we have designed and implemented a system called TeamPhone, which provides smartphones the capabilities of communications in disaster recovery. Specifically, TeamPhone consists of two components: A messaging system and a self-rescue system. The messaging system integrates cellular networking, ad-hoc networking, and opportunistic networking seamlessly, and enables communications among rescue workers. The self-rescue system groups, schedules, and positions the smartphones of trapped survivors. Such a group of smartphones can cooperatively wake up and send out emergency messages in an energy-efficient manner with their location and position information so as to assist rescue operations. We have implemented TeamPhone as a prototype application on the Android platform and deployed it on off-the-shelf smartphones. Experimental results demonstrate that TeamPhone can properly fulfill communication requirements and greatly facilitate rescue operations in disaster recovery.
Width is not additive

We develop the construction suggested by Scharlemann and Thompson in [15] to obtain an infinite family of pairs of knots K and K so that w.K # K 0 / D maxfw.K /; w.K /g . This is the first known example of a pair of knots such that w.K #K/ <w.K/Cw.K/ 2 and it establishes that the lower bound w.K #K/ maxfw.K/; w.K/g obtained in Scharlemann and Schultens [14] is best possible. Furthermore, the knots K provide an example of knots where the number of critical points for the knot in thin position is greater than the number of critical points for the knot in bridge position.
Computational complexity and 3-manifolds and zombies

We show the problem of counting homomorphisms from the fundamental group of a homology 3 –sphere M to a finite, nonabelian simple group G is almost parsimoniously # P –complete, when G is fixed and M is the computational input. In the reduction, we guarantee that every nontrivial homomorphism is a surjection. As a corollary, any nontrivial information about the number of nontrivial homomorphisms is computationally intractable assuming standard conjectures in computer science. In particular, deciding if there is a nontrivial homomorphism is NP –complete. Another corollary is that for any fixed integer m ≥ 5 , it is NP –complete to decide whether M admits a connected m –sheeted covering. Given a classical reversible circuit C , we construct M so that evaluations of C with certain initialization and finalization conditions correspond to homomorphisms π 1 ( M ) → G . An intermediate state of C likewise corresponds to homomorphism π 1 ( Σ g ) → G , where Σ g is a Heegaard surface of M of genus g . We analyze the action on these homomorphisms by the pointed mapping class group MCG ∗ ( Σ g ) and its Torelli subgroup Tor ∗ ( Σ g ) . Using refinements of results of Dunfield and Thurston, we show that the actions of these groups are as large as possible when g is large. Our results and our construction are inspired by universality results in topological quantum computation, even though the present work is nonquantum. One tricky step in the construction is handling an inert “zombie” symbol in the computational alphabet, which corresponds to a trivial homomorphism from the fundamental group of a subsurface of the Heegaard surface.
TOPOLOGICAL ENTANGLEMENT ENTROPY IN THE SECOND LANDAU LEVEL

The entanglement entropy of the incompressible states of a realistic quantum Hall system in the second Landau level is studied by direct diagonalization. The subdominant term of the area law, the topological entanglement entropy, which is believed to carry information about topological order in the ground state, was extracted for filling factors ν = 12/5 and ν = 7/3. While it is difficult to make strong conclusions about ν = 12/5, the ν = 7/3 state appears to be very consistent with the topological entanglement entropy for the k = 4 Read–Rezayi state. The effect of finite thickness corrections to the Coulomb potential used in the direct diagonalization is also systematically studied.
Unifying the Zoo of Jet-driven Stellar Explosions

We present a set of numerical simulations of stellar explosions induced by relativistic jets emanating from a central engine sitting at the center of compact, dying stars. We explore a wide range of durations of the central engine activity, two candidate stellar progenitors, and two possible values of the total energy release. We find that even if the jets are narrowly collimated, their interaction with the star unbinds the stellar material, producing a stellar explosion. We also find that the outcome of the explosion can be very different depending on the duration of the engine activity. Only the longest-lasting engines result in successful gamma-ray bursts. Engines that power jets only for a short time result in relativistic supernova (SN) explosions, akin to observed engine-driven SNe such as SN2009bb. Engines with intermediate durations produce weak gamma-ray bursts, with properties similar to nearby bursts such as GRB 980425. Finally, we find that the engines with the shortest durations, if they exist in nature, produce stellar explosions that lack sizable amounts of relativistic ejecta and are therefore dynamically indistinguishable from ordinary core-collapse SNe.
A characterization of bad approximability

We show that badly approximable vectors are exactly those that cannot, for any inhomogeneous parameter, be inhomogeneously approximated at every monotone divergent rate. This implies in particular that Kurzweil's theorem cannot be restricted to any points in the inhomogeneous part. Our results generalize to weighted approximations, and to higher irrationality exponents.
Distributed algorithms for partially clairvoyant dispatchers

Real-time systems are increasingly appearing in complex and dynamic environments such as cruise controllers, life support systems and nuclear reactors. These systems contain components that sense, control and stabilize the environment towards achieving the mission or target. These consociate components synchronize, compute and control themselves locally or have a centralized component to achieve their mission. Distributed computing techniques improve the overall performance and reliability of large real-time systems with spread components. Partially Clairvoyant scheduling was introduced in Saksena, M., PhD thesis (1994) to determine the schedulability of hard real-time jobs with variable execution times. The problem of deciding the Partially Clairvoyant schedulability of a constrained set of jobs was well studied in Gerber, R., et al., IEEE Trans. Comput. 44(3), 471---479 (1995), Choi, S. and Agrawala, A.K., Real-Time Syst. 19(1), 5---40 (2000), Subramani, K., J. Math. Model. Algorithms 2(2), 97---119 (2003). These algorithms determine the schedulability of a job-set offline and produce a set of dispatch functions for each job in the job-set. The dispatch functions of a job depend on the start and execution times of the jobs sequenced before the job. The dispatching problem is concerned with the online computation of the start time interval of a job such that none of the constraints are violated. In certain situations, the dispatcher fails to dispatch a job as it takes longer to compute the interval within which the job has to be dispatched, this phenomenon is called Loss of Dispatchability. For a job-set of size n, sequential approaches using function lists suffer from two major drawbacks, viz., ?(n) dispatching time and the Loss of Dispatchability phenomenon. Existing approaches to this problem have been along sequential lines, through the use of stored function lists. In this paper, we propose and evaluate three distributed dispatching algorithms for Partially Clairvoyant schedules. For a job-set of size n, the algorithms have dispatch times of O(1) per job. In the first algorithm, one processor executes all the jobs and other processors compute the dispatch functions. This scenario simplifies design and is better in situations where one processor controls all other devices. In the other algorithms, all the processors execute jobs pre-assigned to them and compute the dispatch functions; which is a plausible scenario in distributed controlling.
Probabilistic vortex crossing criterion for superconducting nanowire single-photon detectors

Superconducting nanowire single-photon detectors have emerged as a promising technology for quantum metrology from the mid-infrared to ultraviolet frequencies. Despite recent experimental successes, a predictive model to describe the detection event in these detectors is needed to optimize the detection metrics. Here, we propose a probabilistic criterion for single-photon detection based on single-vortex (flux quanta) crossing the width of the nanowire. Our model makes a connection between the dark counts and photon counts near the detection threshold. The finite-difference calculations demonstrate that a change in the bias current distribution as a result of the photon absorption significantly increases the probability of single-vortex crossing even if the vortex potential barrier has not vanished completely. We estimate the instrument response function and show that the timing uncertainty of this vortex tunneling process corresponds to a fundamental limit in timing jitter of the click event. We demonstrate a trade-space between this intrinsic (quantum) timing jitter, quantum efficiency, and dark count rate in TaN, WSi, and NbN superconducting nanowires at different experimental conditions. Our detection model can also explain the experimental observation of exponential decrease in the quantum efficiency of SNSPDs at lower energies. This leads to a pulse-width dependency in the quantum efficiency, and it can be further used as an experimental test to compare across different detection models.
Critical states embedded in the continuum

We introduce a class of critical states which are embedded in the continuum (CSC) of a one-dimensional optical waveguide array with one non-Hermitian defect. These states are on the verge of being fractal and have real propagation constants. They emerge at a phase transition which is driven by the imaginary refractive index of the defective waveguide and it is accompanied by a mode segregation which reveals analogies with the Dicke super-radiance. Below this point the states are extended while above it they evolve to exponentially localized modes. An addition of a background gain or loss can turn these localized states into bound states in the continuum.
On Spectral and Temporal Variability in Blazars and Gamma-Ray Bursts

A simple model for variability in relativistic plasma outflows is studied, in which nonthermal electrons are continuously and uniformly injected in the comoving frame over a time interval Δt. The evolution of the electron distribution is assumed to be dominated by synchrotron losses, and the energy and time dependence of the synchrotron and synchrotron self-Compton (SSC) fluxes are calculated for a power-law electron injection function with index s=2. The mean time of a flare or pulse measured at photon energy E with respect to the onset of the injection event varies as E-½ and E-1/4 for synchrotron and SSC processes, respectively, until the time approaches the limiting intrinsic mean time (1+z)Δt/(2), where z is the redshift and is the Doppler factor. This dependence is in accord with recent analyses of blazar and gamma-ray burst (GRB) emissions and suggests a method to discriminate between external Compton and SSC models of high-energy gamma radiation from blazars and GRBs. The qualitative behavior of the X-ray spectral index/flux relation observed from BL Lacertae objects can be explained with this model. This demonstrates that synchrotron losses are primarily responsible for the X-ray variability behavior and strengthens a new test for beaming from correlated hard X-ray/TeV observations.
Icy Bodies in the New Solar System

This brief paper summarizes a \key general review" with the same title given at the IAU meeting in Rio de Janeiro. The intent of the review talk was to give a broad and well-illustrated overview of recent work on the icy middle and outer Solar system, in a style interesting for those astronomers whose gaze is otherwise drawn to more distant realms. The intent of this written review is the same.
Eccentric mergers of black holes with spinning neutron stars

We study dynamical capture binary black hole?neutron star (BH?NS) mergers focusing on the effects of the neutron star spin. These events may arise in dense stellar regions, such as globular clusters, where the majority of neutron stars are expected to be rapidly rotating. We initialize the BH?NS systems with positions and velocities corresponding to marginally unbound Newtonian orbits, and evolve them using general-relativistic hydrodynamical simulations. We find that even moderate spins can significantly increase the amount of mass in unbound material. In some of the more extreme cases, there can be up to a third of a solar mass in unbound matter. Similarly, large amounts of tidally stripped material can remain bound and eventually accrete onto the BH?as much as a tenth of a solar mass in some cases. These simulations demonstrate that it is important to treat neutron star spin in order to make reliable predictions of the gravitational wave and electromagnetic transient signals accompanying these sources.
Signatures of Obliquity in Thermal Phase Curves of Hot Jupiters

Recent work suggests that many short-period extrasolar planets may have spin obliquities that are significantly tilted with respect to their orbital planes. These large obliquities are a natural outcome of ``secular spin-orbit resonance'', a configuration in which the planetary spin precession frequency matches the frequency of orbit nodal regression, or a Fourier component thereof. While exoplanet spin obliquities have not yet been measured directly, they may be detectable indirectly through their signatures in various observations, such as photometric measurements across the full phase of a planet's orbit. In this work, we employ a thermal radiative model to explore how large polar tilts affect full-phase light curves, and we discuss the range of unique signatures that are expected to result. We show that the well-studied short-period planets HD 149026 b, WASP-12 b, and CoRoT-2 b all exhibit phase curve features that may arise from being in high-obliquity states. We also constrain the parameters and assess the detectability of hypothetical perturbing planets that could maintain the planets in these states. Among the three planets considered, CoRoT-2 b has the tightest constraints on its proposed obliquity ($45.8^{\circ} \pm 1.4^{\circ}$) and axial orientation. For HD 149026 b, we find no significant evidence for a non-zero obliquity, and the phase curve of WASP-12 b is too complicated by strong tidal distortions for a conclusive assessment.
An optimal rounding for half-integral weighted minimum strongly connected spanning subgraph

Abstract In the weighted minimum strongly connected spanning subgraph ( WMSCSS ) problem we must purchase a minimum-cost strongly connected spanning subgraph of a digraph. We show that half-integral linear program (LP) solutions for WMSCSS can be efficiently rounded to integral solutions at a multiplicative 1.5 cost. This rounding matches a known 1.5 integrality gap lower bound for a half-integral instance. More generally, we show that LP solutions whose non-zero entries are at least a value f > 0 can be rounded at a multiplicative cost of 2 − f .
ACCRETION OF SATURN'S INNER MID-SIZED MOONS FROM A MASSIVE PRIMORDIAL ICE RING.

Saturn's rings are rock-poor, containing 90 to 95% ice by mass. As a group, Saturn's moons interior to and including Tethys are also about 90% ice. Tethys itself contains 40% rock. Here we simulate the evolution of a massive primordial ice-rich ring and the production of satellites as ring material spreads beyond the Roche limit. We describe the Roche-interior ring with an analytic model, and use an N-body code to describe material beyond the Roche limit. We track the accretion and interactions of spawned satellites, including tidal interaction with the planet, assuming a tidal dissipation factor for Saturn of Q ~ 104. We find that ring torques and capture of moons into mutual resonances produces a system of ice-rich inner moons that extends outward to approximately Tethys's orbit in 109 years, even with relatively slow orbital expansion due to tides. The resulting mass and semi-major axis distribution of spawned moons resembles that of Mimas, Enceladus and Tethys. We estimate the mass of rock delivered to the moons by external cometary impactors during a late-heavy bombardment. We find that the inner moons receive a mass in rock comparable to their current total rock content, while Dione and Rhea receive an order-of-magnitude less rock than their current rock content. This suggests that external contamination may have been the primary source of rock in the inner moons, and that Dione and Rhea formed from much more rock-rich source material. Reproducing the distribution of rock among the current inner moons is challenging, and appears to require large impactors and stochasticity and/or the presence of some rock in the initial ring.
Action Principles for Hydro- and Thermo-Dynamics

For all its brilliant success stories, theoretical physics is actually in a lamentable state. The best way to highlight the situation and at the same time point out that it is not difficult to do better — using action principles — is to present several examples.
A FUSE SURVEY OF THE ROTATION RATES OF VERY MASSIVE STARS IN THE SMALL AND LARGE MAGELLANIC CLOUDS

We present projected rotational velocity values for 97 Galactic, 55 SMC, and 106 LMC O-B type stars from archival FUSE observations. The evolved and unevolved samples from each environment are compared through the Kolmogorov-Smirnov test to determine if the distribution of equatorial rotational velocities is metallicity dependent for these massive objects. Stellar interior models predict that massive stars with SMC metallicity will have significantly reduced angular momentum loss on the main sequence compared to their Galactic counterparts. Our results find some support for this prediction but also show that even at Galactic metallicity, evolved and unevolved massive stars have fairly similar fractions of stars with large Vsin i values. Macroturbulent broadening that is present in the spectral features of Galactic evolved massive stars is lower in the LMC and SMC samples. This suggests the processes that lead to macroturbulence are dependent upon metallicity.
Registering large volume serial-section electron microscopy image sets for neural circuit reconstruction using FFT signal whitening

The detailed reconstruction of neural anatomy for connectomics studies requires a combination of resolution and large three-dimensional data capture provided by serial section electron microscopy (ssEM). The convergence of high throughput ssEM imaging and improved tissue preparation methods now allows ssEM capture of complete specimen volumes up to cubic millimeter scale. The resulting multi-terabyte image sets span thousands of serial sections and must be precisely registered into coherent volumetric forms in which neural circuits can be traced and segmented. This paper introduces a Signal Whitening Fourier Transform Image Registration approach (SWiFT-IR) under development at the Pittsburgh Supercomputing Center and its use to align mouse and zebrafish brain datasets acquired using the wafer mapper ssEM imaging technology recently developed at Harvard University. Unlike other methods now used for ssEM registration, SWiFT-IR modifies its spatial frequency response during image matching to maximize a signal-to-noise measure used as its primary indicator of alignment quality. This alignment signal is more robust to rapid variations in biological content and unavoidable data distortions than either phase-only or standard Pearson correlation, thus allowing more precise alignment and statistical confidence. These improvements in turn enable an iterative registration procedure based on projections through multiple sections rather than more typical adjacent-pair matching methods. This projection approach, when coupled with known anatomical constraints and iteratively applied in a multi-resolution pyramid fashion, drives the alignment into a smooth form that properly represents complex and widely varying anatomical content such as the full crosssection zebrafish data.
The supernova progenitor mass distributions of M31 and M33: further evidence for an upper mass limit

Using Hubble Space Telescope photometry to measure star formation histories, we age-date the stellar populations surrounding supernova remnants (SNRs) in M31 and M33. We then apply stellar evolution models to the ages to infer the corresponding masses for their supernova progenitor stars. We analyze 33 M33 SNR progenitors and 29 M31 SNR progenitors in this work. We then combine these measurements with 53 previously published M31 SNR progenitor measurements to bring our total number of progenitor mass estimates to 115. To quantify the mass distributions, we fit power laws of the form dN/dM∝M {sup –α}. Our new larger sample of M31 progenitors follows a distribution with α=4.4{sub −0.4}{sup +0.4}, and the M33 sample follows a distribution with α=3.8{sub −0.5}{sup +0.4}. Thus both samples are consistent within the uncertainties, and the full sample across both galaxies gives α=4.2{sub −0.3}{sup +0.3}. Both the individual and full distributions display a paucity of massive stars when compared to a Salpeter initial mass function, which we would expect to observe if all massive stars exploded as SN that leave behind observable SNR. If we instead fix α = 2.35 and treat the maximum mass as a free parameter, we find M {sub max} ∼ 35-45more » M {sub ☉}, indicative of a potential maximum cutoff mass for SN production. Our results suggest that either SNR surveys are biased against finding objects in the youngest (<10 Myr old) regions, or the highest mass stars do not produce SNe.« less
THE ROLE OF PLATE TECTONIC–CLIMATE COUPLING AND EXPOSED LAND AREA IN THE DEVELOPMENT OF HABITABLE CLIMATES ON ROCKY PLANETS

The long-term carbon cycle is vital for maintaining liquid water oceans on rocky planets due to the negative climate feedbacks involved in silicate weathering. Plate tectonics plays a crucial role in driving the long-term carbon cycle because it is responsible for CO$_2$ degassing at ridges and arcs, the return of CO$_2$ to the mantle through subduction, and supplying fresh, weatherable rock to the surface via uplift and orogeny. However, the presence of plate tectonics itself may depend on climate according to recent geodynamical studies showing that cool surface temperatures are important for maintaining vigorous plate tectonics. Using a simple carbon cycle model, I show that the negative climate feedbacks inherent in the long-term carbon cycle are uninhibited by climate's effect on plate tectonics. Furthermore, initial atmospheric CO$_2$ conditions do not impact the final climate state reached when the carbon cycle comes to equilibrium, as long as liquid water is present and silicate weathering can occur. Thus an initially hot, CO$_2$ rich atmosphere does not prevent the development of a temperate climate and plate tectonics on a planet. However, globally supply-limited weathering does prevent the development of temperate climates on planets with small subaerial land areas and large total CO$_2$ budgets because supply-limited weathering lacks stabilizing climate feedbacks. Planets in the supply-limited regime may become inhospitable for life and could experience significant water loss. Supply-limited weathering is less likely on plate tectonic planets, because plate tectonics promotes high erosion rates and thus a greater supply of bedrock to the surface.
Residual Correlation in Graph Neural Network Regression

A graph neural network transforms features in each vertex's neighborhood into a vector representation of the vertex. Afterward, each vertex's representation is used independently for predicting its label. This standard pipeline implicitly assumes that vertex labels are conditionally independent given their neighborhood features. However, this is a strong assumption, and we show that it is far from true on many real-world graph datasets. Focusing on regression tasks, we find that this conditional independence assumption severely limits predictive power. This should not be that surprising, given that traditional graph-based semi-supervised learning methods such as label propagation work in the opposite fashion by explicitly modeling the correlation in predicted outcomes. Here, we address this problem with an interpretable and efficient framework that can improve any graph neural network architecture simply by exploiting correlation structure in the regression residuals. In particular, we model the joint distribution of residuals on vertices with a parameterized multivariate Gaussian, and estimate the parameters by maximizing the marginal likelihood of the observed labels. Our framework achieves substantially higher accuracy than competing baselines, and the learned parameters can be interpreted as the strength of correlation among connected vertices. Furthermore, we develop linear time algorithms for low-variance, unbiased model parameter estimates, allowing us to scale to large networks. We also provide a basic version of our method that makes stronger assumptions on correlation structure but is painless to implement, often leading to great practical performance with minimal overhead.
A Cheeger inequality for graphs based on a reflection principle

Given a graph with a designated set of boundary vertices, we define a new notion of a Neumann Laplace operator on a graph using a reflection principle. We show that the first eigenvalue of this Neumann graph Laplacian satisfies a Cheeger inequality.
Simple second-order finite differences for elliptic PDEs with discontinuous coefficients and interfaces

In multiphase fluid flow, fluid-structure interaction, and other applications, partial differential equations (PDEs) often arise with discontinuous coefficients and singular sources (e.g., Dirac delta functions). These complexities arise due to changes in material properties at an immersed interface or embedded boundary, which may have an irregular shape. Consequently, the solution and its gradient can be discontinuous, and numerical methods can be difficult to design. Here a new method is presented and analyzed, using a simple formulation of one-dimensional finite differences on a Cartesian grid, allowing for a relatively easy setup for one-, two-, or three-dimensional problems. The derivation is relatively simple and mainly involves centered finite difference formulas, with less reliance on the Taylor series expansions of typical immersed interface method derivations. The method preserves a sharp interface with discontinuous solutions, obtained from a small number of iterations (approximately five) of solving a symmetric linear system with updates to the right-hand side. Second-order accuracy is rigorously proven in one spatial dimension and demonstrated through numerical examples in two and three spatial dimensions. The method is tested here on the variable-coefficient Poisson equation, and it could be extended for use on time-dependent problems of heat transfer, fluid dynamics, or other applications.
Stress Response of Granular Systems

We develop a framework for stress response in two dimensional granular media, with and without friction, that respects vector force balance at the microscopic level. We introduce local gauge degrees of freedom that determine the response of contact forces between constituent grains on a given, disordered, contact network, to external perturbations. By mapping this response to the spectral properties of the graph Laplacian corresponding to the underlying contact network, we show that this naturally leads to spatial localization of forces. We present numerical evidence for localization using exact diagonalization studies of network Laplacians of soft disk packings. Finally, we discuss the role of other constraints, such as torque balance, in determining the stability of a granular packing to external perturbations.
Inference and Modeling with Log-concave Distributions

Log-concave distributions are an attractive choice for modeling and inference, for several reasons: The class of log-concave distributions contains most of the commonly used parametric distributions and thus is a rich and flexible nonparametric class of distributions. Further, the MLE exists and can be computed with readily available algorithms. Thus, no tuning parameter, such as a bandwidth, is necessary for estimation. Due to these attractive properties, there has been considerable recent research activity concerning the theory and applications of log-concave distributions. This article gives a review of these results.
THE ACCRETING WHITE DWARF IN SS CYGNI REVEALED

We have carried out a combined Hubble Space Telescope (HST/GHRS) and Far Ultraviolet Spectroscopic Explorer (FUSE) analysis of the prototype dwarf nova SS Cygni during quiescence. The FUSE and HST spectra were obtained at comparable times after outburst and have matching flux levels where the two spectra overlap. In our synthetic spectral analysis, we have used SS Cygni's accurate HST fine guidance sensor parallax giving d = 166 pc, a newly determined mass for the accreting white dwarf (WD) of M wd = 0.81 M ☉ (lower than the previous widely used 1.2 M ☉) and the reddening (E B–V ) values 0.04 and 0.07 derived from the 2175 A absorption feature in the IUE LWP spectra. From the best-fit model solutions to the combined HST + FUSE spectral energy distribution, we find that the WD is reaching a temperature T eff 45,000-55,000 K in quiescence, assuming log(g) = 8.3 with a solar composition accreted atmosphere. The exact temperature of the WD depends on the reddening assumed and the inclusion of a quiescent low mass accretion rate accretion disk. Accretion disk models alone fit badly in the FUSE range while, and if we take the distance to be a free parameter, the only accretion disk model that fits well is for a discordant distance of at least several hundred parsecs and an accretion rate (~10–8 M ☉ yr–1), which is unacceptably high for a dwarf nova in quiescence. We discuss the implications of the WD's temperature on the time-averaged accretion rate and long-term compressional heating models.
Zooming in on the Coma Cluster with Chandra: Compressed Warm Gas in the Brightest Cluster Galaxies

The Chandra image of the central region of the Coma Cluster reveals that both its dominant galaxies, NGC 4874 and NGC 4889, retain the central parts of their X-ray gas coronae. The interstellar gas with a temperature of 1-2 keV is confined by the hot intergalactic medium of the Coma Cluster into compact clouds (only 3 kpc in radius) containing 108 M☉ of gas. The physical state of the gas in these clouds appears to be determined by a delicate balance between radiative cooling and suppressed (by a factor of 30-100) heat conduction through the interface between these clouds and the hot cluster gas.
Design, Generation, and Validation of Extreme Scale Power-Law Graphs

Massive power-law graphs drive many fields: metagenomics, brain mapping, Internet-of-things, cybersecurity, and sparse machine learning. The development of novel algorithms and systems to process these data requires the design, generation, and validation of enormous graphs with exactly known properties. Such graphs accelerate the proper testing of new algorithms and systems and are a prerequisite for success on real applications. Many random graph generators currently exist that require realizing a graph in order to know its exact properties: number of vertices, number of edges, degree distribution, and number of triangles. Designing graphs using these random graph generators is a time-consuming trial-and-error process. This paper presents a novel approach that uses Kronecker products to allow the exact computation of graph properties prior to graph generation. In addition, when a real graph is desired, it can be generated quickly in memory on a parallel computer with no-interprocessor communication. To test this approach, graphs with 1012 edges are generated on a 40,000+ core supercomputer in 1 second and exactly agree with those predicted by the theory. In addition, to demonstrate the extensibility of this approach, decetta-scale graphs with up to 10^30 edges are simulated in a few minutes on a laptop.
Close-in giant-planet formation via in-situ gas accretion and their natal disk properties

Aims. The origin of close-in Jovian planets is still elusive. We examine the in-situ gas accretion scenario as a formation mechanism of these planets.Methods. We reconstruct natal disk properties from the occurrence rate distribution of close-in giant planets, under the assumption that the occurrence rate may reflect the gas accretion efficiency onto cores of these planets.Results. We find that the resulting gas surface density profile becomes an increasing function of the distance from the central star with some structure at r ≃ 0.1 au. This profile is quite different from the standard minimum-mass solar nebula model, while our profile leads to better reproduction of the population of observed close-in super-Earths based on previous studies. We compute the resulting magnetic field profiles and find that our profiles can be fitted by stellar dipole fields (∝r −3 ) in the vicinity of the central star and large-scale fields (∝r −2 ) at the inner disk regions, either if the isothermal assumption breaks down or if nonideal magnetohydrodynamic effects become important. For both cases, the transition between these two profiles occurs at r ≃ 0.1 au, which corresponds to the period valley of giant exoplanets.Conclusions. Our work provides an opportunity to test the in-situ gas accretion scenario against disk quantities, which may constrain the gas distribution of the minimum-mass extrasolar nebula.