We study the surface fluctuations of a tissue with a dynamics dictated by cell-rearrangement, cell-division, and cell-death processes. Surface fluctuations are calculated in the homeostatic state, where cell division and cell death equilibrate on average. The obtained fluctuation spectrum can be mapped onto several other spectra such as those characterizing incompressible fluids, compressible Maxwell elastomers, or permeable membranes in appropriate asymptotic regimes. Since cell division and cell death are out-of-equilibrium processes, detailed balance is broken, but a generalized fluctuation-response relation is satisfied in terms of appropriate observables. Our work is a first step toward the description of the out-of-equilibrium fluctuations of the surface of a thick epithelium and its dynamical response to external perturbations.

We consider the recent relativistic bit commitment protocol introduced by Lunghi et al. [Phys. Rev. Lett. 115, 030502 (2015)] and present a new security analysis against classical attacks. In particular, while the initial complexity of the protocol scales double exponentially with the commitment time, our analysis shows that the correct dependence is only linear. This has dramatic implications in terms of implementation: in particular, the commitment time can easily be made arbitrarily long, by only requiring both parties to communicate classically and perform efficient classical computation.

We present a guiding principle for designing fermionic Hamiltonians and quantum Monte Carlo (QMC) methods that are free from the infamous sign problem by exploiting the Lie groups and Lie algebras that appear naturally in the Monte Carlo weight of fermionic QMC simulations. Specifically, rigorous mathematical constraints on the determinants involving matrices that lie in the split orthogonal group provide a guideline for sign-free simulations of fermionic models on bipartite lattices. This guiding principle not only unifies the recent solutions of the sign problem based on the continuous-time quantum Monte Carlo methods and the Majorana representation, but also suggests new efficient algorithms to simulate physical systems that were previously prohibitive because of the sign problem.

We determine the distribution of linearly polarized gluons of a dense target at small $x$ by solving the Balitsky–Jalilian-Marian–Iancu–McLerran–Weigert–Leonidov–Kovner rapidity evolution equations. From these solutions, we estimate the amplitude of $\sim \cos 2\varphi$ azimuthal asymmetries in deep inelastic scattering dijet production at high energies. We find sizable long-range in rapidity azimuthal asymmetries with a magnitude in the range of $v_2=⟨\cos 2\varphi ⟩\sim 10\%$.

By means of variational methods and systematic numerical analysis, we demonstrate the existence of metastable solitons in three dimensional (3D) free space, in the context of binary atomic condensates combining contact self-attraction and spin-orbit coupling, which can be engineered by available experimental techniques. Depending on the relative strength of the intra- and intercomponent attraction, the stable solitons feature a semivortex or mixed-mode structure. In spite of the fact that the local cubic self-attraction gives rise to the supercritical collapse in 3D, and hence the setting produces no true ground state, the solitons are stable against small perturbations, motion, and collisions.

A theory is constructed for dense ionic solutions near charged planar walls that is valid for strong interionic correlations. This theory predicts a fluctuation-induced, first-order transition and spontaneous charge density ordering at the interface, in the presence of an otherwise disordered bulk solution. The surface ordering is driven by applied voltage and results in an anomalous differential capacitance, in agreement with recent simulation results and consistent with experimental observations of a wide array of systems. Explicit forms for the charge density profile and capacitance are given. The theory is compared with numerical results for the charge frustrated Ising model, which is also found to exhibit a voltage driven first-order transition.

We have experimentally determined the surface tension-to-shear viscosity ratio (the so-called characteristic velocity) of quasiliquid layers (QLLs) on ice crystal surfaces from their wetting dynamics. Using an advanced optical microscope, whose resolution reaches the molecular level in the height direction, we directly observed the coalescent process of QLLs and followed the relaxation modes of their contact lines. The relaxation dynamics is known to be governed by the characteristic velocity, which allows us to access the physical properties of QLLs in a noninvasive way. Here we quantitatively demonstrate that QLLs, when completely wetting ices, have a thickness of $9\pm 3\mathrm{nm}$ and an approximately 200 times lower characteristic velocity than bulk water, whereas QLLs, when partially wetting ices, have a velocity that is 20 times lower than the bulk. This indicates that ice crystal surfaces significantly affect the physical properties of QLLs localized near the surfaces at a nanometer scale.

A 1D metallic surface state was created on an anisotropic InSb(001) surface covered with Bi. Angle-resolved photoelectron spectroscopy (ARPES) showed a 1D Fermi contour with almost no 2D distortion. Close to the Fermi level ($E_F$), the angle-integrated photoelectron spectra showed power-law scaling with the binding energy and temperature. The ARPES plot above $E_F$, obtained thanks to a thermally broadened Fermi edge at room temperature, showed a 1D state with continuous metallic dispersion across $E_F$ and power-law intensity suppression around $E_F$. These results strongly suggest a Tomonaga-Luttinger liquid on the $\mathrm{Bi}/\mathrm{InSb}(001)$ surface.

We study the electronic structure of bulk single crystals and epitaxial films of ${\mathrm{Fe}}_3{\mathrm{O}}_4$. Fe $2p$ core level spectra show clear differences between hard x-ray (HAX) and soft x-ray photoemission spectroscopy (PES). The bulk-sensitive spectra exhibit temperature ($T$) dependence across the Verwey transition, which is missing in the surface-sensitive spectra. By using an extended impurity Anderson full-multiplet model—and in contrast to an earlier peak assignment—we show that the two distinct Fe species ($A$ and $B$ site) and the charge modulation at the $B$ site are responsible for the newly found double peaks in the main peak above $T_V$ and its $T$-dependent evolution. The Fe $2p$ HAXPES spectra show a clear magnetic circular dichroism (MCD) in the metallic phase of magnetized 100-nm-thick films. The model calculations also reproduce the MCD and identify the contributions from magnetically distinct $A$ and $B$ sites. Valence band HAXPES shows a finite density of states at $E_F$ for the polaronic half metal with a remnant order above $T_V$ and a clear gap formation below $T_V$. The results indicate that the Verwey transition is driven by changes in the strongly correlated and magnetically active $B$-site electronic states, consistent with resistivity and optical spectra.

Large magnetic anisotropy energy (MAE) is desirable and critical for nanoscale magnetic devices. Here, using ligand-field level diagrams and density functional calculations, we well explain the very recent discovery [I. G. Rau et al., Science 344, 988 (2014)] that an individual Co adatom on a MgO (001) surface has a large MAE of more than 60 meV. More importantly, we predict that a giant MAE up to 110 meV could be realized for Ru adatoms on MgO (001), and even more for the Os adatoms (208 meV). This is a joint effect of the special ligand field, orbital multiplet, and significant spin-orbit interaction, in the intermediate-spin state of the Ru or Os adatoms on top of the surface oxygens. The giant MAE could provide a route to atomic scale memory.

We present a hydrodynamic model of flocking that generalizes the familiar Toner-Tu equations to incorporate turning inertia of well-polarized flocks. The continuum equations controlled by only two dimensionless parameters, orientational inertia and alignment strength, are derived by coarse-graining the inertial spin model recently proposed by Cavagna et al. The interplay between orientational inertia and bend elasticity of the flock yields anisotropic spin waves that mediate the propagation of turning information throughout the flock. The coupling between spin-current density to the local vorticity field through a nonlinear friction gives rise to a hydrodynamic mode with angular-dependent propagation speed at long wavelengths. This mode becomes unstable as a result of the growth of bend and splay deformations augmented by the spin wave, signaling the transition to complex spatiotemporal patterns of continuously turning and swirling flocks.

Interactions between microorganisms and solid boundaries play an important role in biological processes, such as egg fertilization, biofilm formation, and soil colonization, where microswimmers move within a structured environment. Despite recent efforts to understand their origin, it is not clear whether these interactions can be understood as being fundamentally of hydrodynamic origin or hinging on the swimmer’s direct contact with the obstacle. Using a combination of experiments and simulations, here we study in detail the interaction of the biflagellate green alga Chlamydomonas reinhardtii, widely used as a model puller microorganism, with convex obstacles, a geometry ideally suited to highlight the different roles of steric and hydrodynamic effects. Our results reveal that both kinds of forces are crucial for the correct description of the interaction of this class of flagellated microorganisms with boundaries.

Living cells can enhance their fitness by anticipating environmental change. We study how accurately linear signaling networks in cells can predict future signals. We find that maximal predictive power results from a combination of input-noise suppression, linear extrapolation, and selective readout of correlated past signal values. Single-layer networks generate exponential response kernels, which suffice to predict Markovian signals optimally. Multilayer networks allow oscillatory kernels that can optimally predict non-Markovian signals. At low noise, these kernels exploit the signal derivative for extrapolation, while at high noise, they capitalize on signal values in the past that are strongly correlated with the future signal. We show how the common motifs of negative feedback and incoherent feed-forward can implement these optimal response functions. Simulations reveal that E. coli can reliably predict concentration changes for chemotaxis, and that the integration time of its response kernel arises from a trade-off between rapid response and noise suppression.

We show that the steady-state entropy production rate of a stochastic process is inversely proportional to the minimal time needed to decide on the direction of the arrow of time. Here we apply Wald’s sequential probability ratio test to optimally decide on the direction of time’s arrow in stationary Markov processes. Furthermore, the steady-state entropy production rate can be estimated using mean first-passage times of suitable physical variables. We derive a first-passage time fluctuation theorem which implies that the decision time distributions for correct and wrong decisions are equal. Our results are illustrated by numerical simulations of two simple examples of nonequilibrium processes.

We derive a new flavor symmetry relation for the determination of the weak phase $\beta ={\varphi }_1$ from time-dependent $CP$ asymmetries and $B\to J/\psi P$ decay rates. In this relation, the contributions to $\sin 2\beta$ proportional to $V_{ub}$ are parametrically suppressed compared to the contributions in the $B\to J/\psi K^0$ time-dependent $CP$ asymmetry alone. This relation uses only $SU(3)$ flavor symmetry, and does not require further diagrammatic assumptions. The current data either fluctuate at the $2\sigma$ level from expectations, or may hint at effects of unexpected magnitude from contributions proportional to $V_{ub}$ or from isospin breaking.

We find new sum rules between direct $CP$ asymmetries in $D$ meson decays with coefficients that can be determined from a global fit to branching ratio data. Our sum rules eliminate the penguin topologies $P$ and $PA$, which cannot be determined from branching ratios. In this way, we can make predictions about direct $CP$ asymmetries in the standard model without ad hoc assumptions on the sizes of penguin diagrams. We consistently include first-order ${\mathrm{SU}(3)}_F$ breaking in the topological amplitudes extracted from the branching ratios. By confronting our sum rules with future precise data from LHCb and Belle II, one will identify or constrain new-physics contributions to $P$ or $PA$. The first sum rule correlates the $CP$ asymmetries $a_{CP}^{\text{dir}}$ in $D^0\to K^{+}{K}^{-}$, $D^0\to {\pi }^{+}{\pi }^{-}$, and $D^0\to {\pi }^0{\pi }^0$. We study the region of the $a_{CP}^{\text{dir}}(D^0\to {\pi }^{+}{\pi }^{-})-a_{CP}^{\text{dir}}(D^0\to {\pi }^0{\pi }^0)$ plane allowed by current data and find that our sum rule excludes more than half of the allowed region at 95% C.L. Our second sum rule correlates the direct $CP$ asymmetries in $D^{+}\to {\overline{K}}^0{K}^{+}$, $D_s^{+}\to K^0{\pi }^{+}$, and $D_s^{+}\to K^{+}{\pi }^0$.