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The science of literature : essays on an incalculable difference
Do literary texts provide distinctive access to the history of science? Is the study of literature based on scientific procedures? Is there a connection between scientific processes and literary forms? The essays in this collection show how literary and scientific texts from the late 18th to the late 19th centuries revolve around these questions. What emerges is a picture of the mutual dependence and the incalculable difference between literature and science in the period of their modern formation. -- Provided by publisher
Book
Stabilizing complex Langevin for real-time gauge theories with an anisotropic kernel
A
bstract
The complex Langevin (CL) method is a promising approach to overcome the sign problem that occurs in real-time formulations of quantum field theories. Using the Schwinger-Keldysh formalism, we study SU(
N
c
) gauge theories with CL. We observe that current stabilization techniques are insufficient to obtain correct results. Therefore, we revise the discretization of the CL equations on complex time contours, find a time reflection symmetric formulation and introduce a novel anisotropic kernel that enables CL simulations on discretized complex time paths. Applying it to SU(2) Yang-Mills theory in 3+1 dimensions, we obtain unprecedentedly stable results that we validate using additional observables and that can be systematically improved. For the first time, we are able to simulate non-Abelian gauge theory on time contours whose real-time extent exceeds its inverse temperature. Thus, our approach may pave the way towards an ab-initio real-time framework of QCD in and out of equilibrium with a potentially large impact on the phenomenology of heavy-ion collisions.
Journal Article
Implicit schemes for real-time lattice gauge theory
We develop new gauge-covariant implicit numerical schemes for classical real-time lattice gauge theory. A new semi-implicit scheme is used to cure a numerical instability encountered in three-dimensional classical Yang-Mills simulations of heavy-ion collisions by allowing for wave propagation along one lattice direction free of numerical dispersion. We show that the scheme is gauge covariant and that the Gauss constraint is conserved even for large time steps.
Journal Article
Applications of Lattice Gauge Equivariant Neural Networks
The introduction of relevant physical information into neural network architectures has become a widely used and successful strategy for improving their performance. In lattice gauge theories, such information can be identified with gauge symmetries, which are incorporated into the network layers of our recently proposed Lattice Gauge Equivariant Convolutional Neural Networks (L-CNNs). L-CNNs can generalize better to differently sized lattices than traditional neural networks and are by construction equivariant under lattice gauge transformations. In these proceedings, we present our progress on possible applications of L-CNNs to Wilson flow or continuous normalizing flow. Our methods are based on neural ordinary differential equations which allow us to modify link configurations in a gauge equivariant manner. For simplicity, we focus on simple toy models to test these ideas in practice.
Journal Article
Network manipulation algorithm based on inexact alternating minimization
In this paper, we present a network manipulation algorithm based on an alternating minimization scheme from Nesterov (Soft Comput 1–12, 2020). In our context, the alternative process mimics the natural behavior of agents and organizations operating on a network. By selecting starting distributions, the organizations determine the short-term dynamics of the network. While choosing an organization in accordance with their manipulation goals, agents are prone to errors. This rational inattentive behavior leads to discrete choice probabilities. We extend the analysis of our algorithm to the inexact case, where the corresponding subproblems can only be solved with numerical inaccuracies. The parameters reflecting the imperfect behavior of agents and the credibility of organizations, as well as the condition number of the network transition matrix have a significant impact on the convergence of our algorithm. Namely, they turn out not only to improve the rate of convergence, but also to reduce the accumulated errors. From the mathematical perspective, this is due to the induced strong convexity of an appropriate potential function.
Journal Article
A major trade-off between growth and defense in Arabidopsis thaliana can vanish in field conditions
When wild plants defend themselves from pathogens, this often comes with a trade-off: the same genes that protect a plant from disease can also reduce its growth and fecundity in the absence of pathogens. One protein implicated in a major growth-defense trade-off is ACCELERATED CELL DEATH 6 (ACD6), an ion channel that modulates salicylic acid (SA) synthesis to potentiate a wide range of defenses. Wild Arabidopsis thaliana populations maintain significant functional variation at the ACD6 locus, with some alleles making the protein hyperactive. In the greenhouse, plants with hyperactive ACD6 alleles are resistant to diverse pathogens, yet they are of smaller stature, their leaves senesce earlier, and they set fewer seeds compared to plants with the standard allele. We hypothesized that ACD6 hyperactivity would not only affect the growth of microbial pathogens but also more generally change leaf microbiome assembly. To test this in an ecologically meaningful context, we compared plants with hyperactive, standard, and defective ACD6 alleles in the same field-collected soil, both outdoors and in naturally lit and climate-controlled indoor conditions, taking advantage of near-isogenic lines as well as a natural accession and a CRISPR-edited derivative. We surveyed visual phenotypes, gene expression, hormone levels, seed production, and the microbiome in each environment. The genetic precision of CRISPR-edited plants allowed us to conclude that ACD6 genotype had no effect on mature field plants in our setting, despite reproducibly dramatic effects on greenhouse plants. We conclude that additional abiotic and/or microbial signals present outdoors—but not in the greenhouse—greatly modulate ACD6 activity. This raises the possibility that the fitness costs of other commonly studied immune system genes may be grossly misjudged without field studies.
Journal Article
On transverse momentum broadening in real-time lattice simulations of the glasma and in the weak-field limit
In these proceedings, we report on our numerical lattice simulations of partons traversing the boost-invariant, non-perturbative glasma as created at the early stages of collisions at RHIC and LHC. Since these highly energetic partons are produced from hard scatterings during heavy-ion collisions, they are already affected by the first stage of the medium's time evolution, the glasma, which is the pre-equilibrium precursor state of the quark-gluon plasma. We find that partons quickly accumulate transverse momentum up to the saturation momentum during the glasma stage. Moreover, we observe an interesting anisotropy in transverse momentum broadening of partons with larger broadening in the rapidity than in the azimuthal direction. Its origin can be related to correlations among the longitudinal color-electric and color-magnetic flux tubes in the initial state of the glasma. We compare these observations to the semi-analytic results obtained by a weak-field approximation, where we also find such an anisotropy in a parton's transverse momentum broadening.
Journal Article
The impact of glasma on heavy quark spectra and correlations
We investigate the effect of the glasma classical color fields, produced in the very early stage of heavy-ion collisions, on the transport of heavy quarks. The glasma fields evolve according to the classical Yang-Mills equations, while the dynamics of heavy quarks is described by Wong’s equations. We numerically solve these equations and extract observables sensitive to the initial glasma stage. The heavy quark nuclear modification factor R AA is affected by the glasma but the effect is moderate compared to the nPDF contribution. Our main finding is that the glasma has a large impact on the azimuthal correlation between QQ pairs, initially produced back-to-back.
Journal Article
Studying the 3+1D structure of the Glasma using the weak field approximation
We extend the weak field approximation for the Glasma beyond the boost-invariant approximation, which allows us to compute rapidity-dependent observables in the early stages of heavy-ion collisions. We show that in the limit of small fields, the weak field approximation agrees quantitatively with non-perturbative lattice simulations. Furthermore, we demonstrate that the rapidity profile of the transverse pressure is determined by longitudinal color correlations within the colliding nuclei.
Journal Article
Preserving gauge invariance in neural networks
In these proceedings we present lattice gauge equivariant convolutional neural networks (L-CNNs) which are able to process data from lattice gauge theory simulations while exactly preserving gauge symmetry. We review aspects of the architecture and show how L-CNNs can represent a large class of gauge invariant and equivariant functions on the lattice. We compare the performance of L-CNNs and non-equivariant networks using a non-linear regression problem and demonstrate how gauge invariance is broken for non-equivariant models.
Journal Article