Navigation of micro-swimmers in steady flow: the importance of symmetries

Marine micro-organisms must cope with complex flow patterns and even turbulence as they navigate the ocean. To survive they must avoid predation and find efficient energy sources. A major difficulty in analysing possible survival strategies is that the time series of environmental cues in nonlinear flow is complex and that it depends on the decisions taken by the organism. One way of determining and evaluating optimal strategies is reinforcement learning. In a proof-of-principle study, Colabrese et al. (Phys. Rev. Lett., vol. 118, 2017, 158004) used this method to find out how a micro-swimmer in a vortex flow can navigate towards the surface as quickly as possible, given a fixed swimming speed. The swimmer measured its instantaneous swimming direction and the local flow vorticity in the laboratory frame, and reacted to these cues by swimming either left, right, up or down. However, usually a motile micro-organism measures the local flow rather than global information, and it can only react in relation to the local flow because, in general, it cannot access global information (such as up or down in the laboratory frame). Here we analyse optimal strategies with local signals and actions that do not refer to the laboratory frame. We demonstrate that symmetry breaking is required to find such strategies. Using reinforcement learning, we analyse the emerging strategies for different sets of environmental cues that micro-organisms are known to measure.

Wave-packet continuum discretisation for nucleon-nucleon scattering predictions

In this paper we analyse the efficiency, precision, and accuracy of computing elastic nucleon-nucleon (\NN) scattering amplitudes with the wave-packet continuum discretisation method (\wpcd). This method provides approximate scattering solutions at multiple scattering energies simultaneously. We therefore utilise a graphics processing unit (GPU) to explore the benefits of this inherent parallelism. From a theoretical perspective, the \wpcd{} method promises a speedup compared to a standard matrix-inversion method. We use the chiral NNLO$_{\rm opt}$ interaction to demonstrate that \wpcd{} enables efficient computation of \NN{} scattering amplitudes provided one can tolerate an averaged method error of $~1-5$ mb in the total cross section at scattering energies $0-350$ MeV in the laboratory frame of reference. Considering only scattering energies $\sim40-350$ MeV, we find a smaller method error of $\lesssim 1-2$ mb. By increasing the number of wave-packets we can further reduce the overall method error. However, the parallel leverage of the \wpcd{} method will be offset by the increased size of the resulting discretisation mesh. In practice, a GPU-implementation is mainly advantageous for matrices that fit in the fast on-chip shared memory. We find that \wpcd{} is a promising method for computationally efficient, statistical analyses of nuclear interactions from effective field theory, where we can utilise Bayesian inference methods to incorporate relevant uncertainties.

Probing gluon number density with electron-dijet correlations at EIC

We propose a novel way of studying the gluon number density (the so-called Weizsäcker–Williams gluon distribution) using the planned Electron Ion Collider. Namely, with the help of the azimuthal correlations between the total transverse momentum of the dijet system and the scattered electron, we examine an interplay between the effect of the soft gluon emissions (the Sudakov form factor) and the gluon saturation effects. The kinematic cuts are chosen such that the dijet system is produced in the forward direction in the laboratory frame, which provides an upper bound on the probed longitudinal fractions of the hadron momentum carried by scattered gluons. Further cuts enable us to use the factorization formalism that directly involves the unpolarized Weizsäcker–Williams gluon distribution. We find this observable to be very sensitive to the soft gluon emission and moderately sensitive to the gluon saturation.

New physics and the tau polarization vector in b → $$ \mathrm{c}\tau {\overline{\nu}}_{\tau } $$ decays

For a general Hb → $$ {H}_c\tau {\overline{\nu}}_{\tau } $$ H c τ ν ¯ τ decay we analyze the role of the τ polarization vector $$ {\mathcal{P}}^{\mu } $$ P μ in the context of lepton flavor universality violation studies. We use a general phenomenological approach that includes, in addition to the Standard Model (SM) contribution, vector, axial, scalar, pseudoscalar and tensor new physics (NP) terms which strength is governed by, complex in general, Wilson coefficients. We show that both in the laboratory frame, where the initial hadron is at rest, and in the center of mass of the two final leptons, a $$ \overrightarrow{\mathcal{P}} $$ P → component perpendicular to the plane defined by the three-momenta of the final hadron and the τ lepton is only possible for complex Wilson coefficients, being a clear signal for physics beyond the SM as well as time reversal (or CP-symmetry) violation. We make specific evaluations of the different polarization vector components for the Λb → Λc, $$ {\overline{B}}_c $$ B ¯ c → ηc, J/ψ and $$ \overline{B} $$ B ¯ → D(*) semileptonic decays, and describe NP effects in the complete two-dimensional space associated with the independent kinematic variables on which the polarization vector depends. We find that the detailed study of $$ {\mathcal{P}}^{\mu } $$ P μ has great potential to discriminate between different NP scenarios for 0− → 0− decays, but also for Λb → Λc transitions. For this latter reaction, we pay special attention to corrections to the SM predictions derived from complex Wilson coefficients contributions.

Modeling the Dynamics of Heavy-Ion Collisions with a Hydrodynamic Model Using a Graphics Processor

Dense bulk matter is formed during heavy-ion collision and expands towards a vacuum. It behaves as a perfect fluid, described by relativistic hydrodynamics. In order to study initial condition fluctuation and properties of jet propagation in dense hot matter, we assume a Cartesian laboratory frame with several million cells in a stencil with high-accuracy data volume grids. Employing numerical algorithms to solve hydrodynamic equations in such an assumption requires a lot of computing power. Hydrodynamic simulations of nucleus + nucleus interactions in the range of energies of the Large Hadron Collider (LHC) are carried out using our program, which uses Graphics Processing Units (GPUs) and Compute Unified Device Architecture (CUDA). In this work, we focused on transforming hydrodynamic quantities into kinetic descriptions. We implemented the hypersurface freeze-out conditions using marching cubes techniques. We developed freeze-out procedures to obtain the momentum distributions of particles on the hypersurface. The final particle distributions, elliptic flow, and higher harmonics are comparable to the experimental LHC data.

Bootstrap Aggregation for Model Selection in the Model-free Formalism

The ability to make robust inferences about the dynamics of biological macromolecules using NMR spectroscopy depends heavily on the application of appropriate theoretical models for nuclear spin relaxation. Data analysis for NMR laboratory-frame relaxation experiments typically involves selecting one of several model-free spectral density functions using a bias-corrected fitness test. Here, advances in statistical model selection theory, termed bootstrap aggregation or bagging, are applied to 15N spin relaxation data, developing a multimodel inference solution to the model-free selection problem. The approach is illustrated using data sets recorded at four static magnetic fields for the bZip domain of the S. cerevisiae transcription factor GCN4.

Molecular structure retrieval directly from laboratory-frame photoelectron spectra in laser-induced electron diffraction

Ubiquitous to most molecular scattering methods is the challenge to retrieve bond distance and angle from the scattering signals since this requires convergence of pattern matching algorithms or fitting methods. This problem is typically exacerbated when imaging larger molecules or for dynamic systems with little a priori knowledge. Here, we employ laser-induced electron diffraction (LIED) which is a powerful means to determine the precise atomic configuration of an isolated gas-phase molecule with picometre spatial and attosecond temporal precision. We introduce a simple molecular retrieval method, which is based only on the identification of critical points in the oscillating molecular interference scattering signal that is extracted directly from the laboratory-frame photoelectron spectrum. The method is compared with a Fourier-based retrieval method, and we show that both methods correctly retrieve the asymmetrically stretched and bent field-dressed configuration of the asymmetric top molecule carbonyl sulfide (OCS), which is confirmed by our quantum-classical calculations.

Measurements of $\overline{\nu}_{\mu}$ and $\overline{\nu}_{\mu} + \nu_{\mu}$ charged-current cross-sections without detected pions or protons on water and hydrocarbon at a mean anti-neutrino energy of 0.86 GeV

We report measurements of the flux-integrated $\overline{\nu}_\mu$ and $\overline{\nu}_\mu+\nu_\mu$ charged-current cross-sections on water and hydrocarbon targets using the T2K anti-neutrino beam with a mean beam energy of 0.86 GeV. The signal is defined as the (anti-)neutrino charged-current interaction with one induced $\mu^\pm$ and no detected charged pion or proton. These measurements are performed using a new WAGASCI module recently added to the T2K setup in combination with the INGRID Proton Module. The phase space of muons is restricted to the high-detection efficiency region, $p_{\mu}>400~{\rm MeV}/c$ and $\theta_{\mu}<30^{\circ}$, in the laboratory frame. An absence of pions and protons in the detectable phase spaces of $p_{\pi}>200~{\rm MeV}/c$, $\theta_{\pi}<70^{\circ}$ and $p_{\rm p}>600~{\rm MeV}/c$, $\theta_{\rm p}<70^{\circ}$ is required. In this paper, both the $\overline{\nu}_\mu$ cross-sections and $\overline{\nu}_\mu+\nu_\mu$ cross-sections on water and hydrocarbon targets and their ratios are provided by using the D’Agostini unfolding method. The results of the integrated $\overline{\nu}_\mu$ cross-section measurements over this phase space are $\sigma_{\rm H_{2}O}=(1.082\pm0.068(\rm stat.)^{+0.145}_{-0.128}(\rm syst.)) \times 10^{-39}\,{\rm cm^{2} / nucleon}$, $\sigma_{\rm CH}=(1.096\pm0.054(\rm stat.)^{+0.132}_{-0.117}(\rm syst.)) \times 10^{-39}\,{\rm cm^{2} / nucleon}$, and $\sigma_{\rm H_{2}O}/\sigma_{\rm CH} = 0.987\pm0.078(\rm stat.)^{+0.093}_{-0.090}(\rm syst.)$. The $\overline{\nu}_\mu+\nu_\mu$ cross-section is $\sigma_{\rm H_{2}O} = (1.155\pm0.064(\rm stat.)^{+0.148}_{-0.129}(\rm syst.)) \times 10^{-39}\,{\rm cm^{2} / nucleon}$, $\sigma_{\rm CH}=(1.159\pm0.049(\rm stat.)^{+0.129}_{-0.115}(\rm syst.)) \times 10^{-39}\,{\rm cm^{2} / nucleon}$, and $\sigma_{\rm H_{2}O}/\sigma_{\rm CH}=0.996\pm0.069(\rm stat.)^{+0.083}_{-0.078}(\rm syst.)$.