Bipedal Hopping: Reduced-order Model Embedding via Optimization-based Control

This paper presents the design and validation of controlling hopping on the 3D bipedal robot Cassie. A spring-mass model is identified from the kinematics and compliance of the robot. The spring stiffness and damping are encapsulated by the leg length, thus actuating the leg length can create and control hopping behaviors. Trajectory optimization via direct collocation is performed on the spring-mass model to plan jumping and landing motions. The leg length trajectories are utilized as desired outputs to synthesize a control Lyapunov function based quadratic program (CLF-QP). Centroidal angular momentum, taking as an addition output in the CLF-QP, is also stabilized in the jumping phase to prevent whole body rotation in the underactuated flight phase. The solution to the CLF-QP is a nonlinear feedback control law that achieves dynamic jumping behaviors on bipedal robots with compliance. The framework presented in this paper is verified experimentally on the bipedal robot Cassie.Comment: 8 pages, 7 figures, accepted by IROS 201

A microscopic model for solidification

We present a novel picture of a non isothermal solidification process starting from a molecular level, where the microscopic origin of the basic mechanisms and of the instabilities characterizing the approach to equilibrium is rendered more apparent than in existing approaches based on coarse grained free energy functionals \`a la Landau. The system is composed by a lattice of Potts spins, which change their state according to the stochastic dynamics proposed some time ago by Creutz. Such a method is extended to include the presence of latent heat and thermal conduction. Not only the model agrees with previous continuum treatments, but it allows to introduce in a consistent fashion the microscopic stochastic fluctuations. These play an important role in nucleating the growing solid phase in the melt. The approach is also very satisfactory from the quantitative point of view since the relevant growth regimes are fully characterized in terms of scaling exponents.Comment: 7 pages Latex +3 figures.p

Quantum storage of polarization qubits in birefringent and anisotropically absorbing materials

Storage of quantum information encoded into true single photons is an essential constituent of long-distance quantum communication based on quantum repeaters and of optical quantum information processing. The storage of photonic polarization qubits is, however, complicated by the fact that many materials are birefringent and have polarization-dependent absorption. Here we present and demonstrate a simple scheme that allows compensating for these polarization effects. The scheme is demonstrated using a solid-state quantum memory implemented with an ensemble of rare-earth ions doped into a biaxial yttrium orthosilicate ($Y_2SiO_5$) crystal. Heralded single photons generated from a filtered spontaneous parametric downconversion source are stored, and quantum state tomography of the retrieved polarization state reveals an average fidelity of $97.5 \pm 0.4$, which is significantly higher than what is achievable with a measure-and-prepare strategy.Comment: 7 pages, 3 figures, 1 table, corrected typos and added ref. 3

Sample variance in the local measurements of the Hubble constant

The current $>3\sigma$ tension between the Hubble constant $H_0$ measured from local distance indicators and from cosmic microwave background is one of the most highly debated issues in cosmology, as it possibly indicates new physics or unknown systematics. In this work, we explore whether this tension can be alleviated by the sample variance in the local measurements, which use a small fraction of the Hubble volume. We use a large-volume cosmological $N$-body simulation to model the local measurements and to quantify the variance due to local density fluctuations and sample selection. We explicitly take into account the inhomogeneous spatial distribution of type Ia supernovae. Despite the faithful modelling of the observations, our results confirm previous findings that sample variance in the local Hubble constant $(H_0^{\rm loc})$ measurements is small; we find $\sigma(H_0^{\rm loc})=0.31\,{\rm km\ s^{-1}Mpc^{-1}}$, a nearly negligible fraction of the$\sim6\,{\rm km\ s^{-1}Mpc^{-1}}$necessary to explain the difference between the local and the global$H_0$measurements. While the$H_0$tension could in principle be explained by our local neighbourhood being a underdense region of radius$\sim 150 \,\rm Mpc$, the extreme required underdensity of such a void$(\delta\simeq -0.8)$makes it very unlikely in a$\Lambda$CDM universe, and it also violates existing observational constraints. Therefore, sample variance in a$\Lambda$CDM universe cannot appreciably alleviate the tension in$H_0$ measurements even after taking into account the inhomogeneous selection of type Ia supernovae.Comment: 10 pages, 6 figures, 1 table; main result in Figure 3; replaced to match published versio

Machine Learning tools for global PDF fits

The use of machine learning algorithms in theoretical and experimental high-energy physics has experienced an impressive progress in recent years, with applications from trigger selection to jet substructure classification and detector simulation among many others. In this contribution, we review the machine learning tools used in the NNPDF family of global QCD analyses. These include multi-layer feed-forward neural networks for the model-independent parametrisation of parton distributions and fragmentation functions, genetic and covariance matrix adaptation algorithms for training and optimisation, and closure testing for the systematic validation of the fitting methodology.Comment: 12 pages, 9 figures, to appear in the proceedings of the XXIIIth Quark Confinement and the Hadron Spectrum conference, 1-6 August 2018, University of Maynooth, Irelan