Phase transitions and anomalous normal state in superconductors with broken time reversal symmetry

Using Monte Carlo simulations, we explore the phase diagram and the phase transitions in \groupUZ $n$-band superconductors with spontaneously broken time-reversal symmetry (also termed $s+is$ superconductors), focusing on the three-band case. In the limit of infinite penetration length, the system under consideration can, for a certain parameter regime, have a single first order phase transition from a \groupUZ broken state to a normal state due to a nontrivial interplay between \groupU vortices and \groupZ domain walls. This regime may also apply to multicomponent superfluids. For other parameters, when the free energy of the domain walls is low, the system undergoes a restoration of broken \groupZ time reversal symmetry at temperatures lower than the temperature of the superconducting phase transition.{We show that inclusion of fluctuations can strongly suppress the temperature of the \groupZ-transition when frustration is weak. The main result of our paper is that} for relatively short magnetic field penetration lengths, the system has a superconducting phase transition at a temperature lower than the temperature of the restoration of the broken \groupZ symmetry. Thus, there appears a new phase which is \groupU-symmetric, but breaks \groupZ time reversal symmetry, an anomalous dissipative (metallic) state.Comment: 12 pages, 12 figures, submitted to Physical Review

Annotating otoliths with a deep generative model

Otoliths are a central information source for fish ecology and stock management, conveying important data about age and other life history for individual fish. Traditionally, interpretation of otoliths has required skilled expert readers, but recently deep learning classification and regression models have been trained to extract fish age from images of otoliths from a variety of species. Despite high accuracy in many cases, the adoption of such models in fisheries management has been slow. One reason may be that the underlying mechanisms the model uses to derive its results from the data are opaque, and this lack of legibility makes it challenging to build sufficient trust in the results. Here, we implement a deep learning model that instead of age predicts the location of annotation marks for each of the annuli. This allows an expert to evaluate the model’s performance in detail. The quality of the annotations was judged by a panel of four expert otolith readers in a double-blinded randomized survey. Using a scale from 1 to 5, the generated marks received an average quality score of 4.22, whereas expert annotations received an average score of 4.33. By counting the marks to determine fish age, we obtained an agreement between expert and model annotations of 64% on our test set, which running the model stochastically increased to 69%. Stochastic sampling yields further benefits, including an explicit measure of the model’s uncertainty, the post hoc likelihood of the different age classes for each otolith, and a set of alternative annotation sequences that highlight the structure of the annuli.publishedVersio

Inductive Bias for Emergent Communication in a Continuous Setting

We study emergent communication in a multi-agent reinforcement learning setting, where the agents solve cooperative tasks and have access to a communication channel. The communication channel may consist of either discrete symbols or continuous variables. We introduce an inductive bias to aid with the emergence of good communication protocols for continuous messages, and we look at the effect this type of inductive bias has for continuous and discrete messages in itself or when used in combination with reinforcement learning. We demonstrate that this type of inductive bias has a beneficial effect on the communication protocols learnt in two toy environments, Negotiation and Sequence Guess.Comment: NIPS 2023 Preprint. 12 pages, 5 figures, 3 table

Topological semimetals protected by off-centered symmetries in nonsymmorphic crystals

Topological semimetals have energy bands near the Fermi energy sticking together at isolated points/lines/planes in the momentum space, which are often accompanied by stable surface states and intriguing bulk topological responses. Although it has been known that certain crystalline symmetries play an important role in protecting band degeneracy, a general recipe for stabilizing the degeneracy, especially in the presence of spin-orbit coupling, is still lacking. Herewe showthat a class of novel topological semimetals with point/line nodes can emerge in the presence of an off-centered rotation/mirror symmetry whose symmetry line/plane is displaced from the center of other symmorphic symmetries in nonsymmorphic crystals. Due to the partial translation perpendicular to the rotation axis/mirror plane, an off-centered rotation/mirror symmetry always forces two energy bands to stick together and form a doublet pair in the relevant invariant line/plane in momentum space. Such a doublet pair provides a basic building block for emerging topological semimetals with point/line nodes in systems with strong spin-orbit coupling. ©2017 American Physical Society121221sciescopu

Time Reversal Symmetry Breakdown in Normal and Superconducting States in Frustrated Three-Band Systems

We discuss the phase diagram and phase transitions in U(1)×Z2 three-band superconductors with broken time reversal symmetry. We find that beyond mean-field approximation and for sufficiently strong frustration of interband interactions there appears an unusual metallic state precursory to a superconducting phase transition. In that state, the system is not superconducting. Nonetheless, it features a spontaneously broken Z2 time reversal symmetry. By contrast, for weak frustration of interband coupling the energy of a domain wall between different Z2 states is low and thus fluctuations restore broken time reversal symmetry in the superconducting state at low temperatures