Tracking a randomly varying optical phase is a key task in metrology, with applications in optical communication. The best precision for optical-phase tracking has until now been limited by the quantum vacuum fluctuations of coherent light. Here, we surpass this coherent-state limit by using a continuous-wave beam in a phase-squeezed quantum state. Unlike in previous squeezing-enhanced metrology, restricted to phases with very small variation, the best tracking precision (for a fixed light intensity) is achieved for a finite degree of squeezing because of Heisenberg's uncertainty principle. By optimizing the squeezing, we track the phase with a mean square error 15 ± 4% below the coherent-state limit.

Cells of Flavobacterium johnsoniae and of many other members of the phylum Bacteroidetes exhibit rapid gliding motility over surfaces by a unique mechanism. These cells do not have flagella or pili; instead, they rely on a novel motility apparatus composed of Gld and Spr proteins. SprB, a 669-kDa cell-surface adhesin, is required for efficient gliding. SprB was visualized by electron microscopy as thin 150-nm-long filaments extending from the cell surface. Fluorescence microscopy revealed movement of SprB proteins toward the poles of the cell at ∼2 μm/s. The fluorescent signals appeared to migrate around the pole and continue at the same speed toward the opposite pole along an apparent left-handed helical closed loop. Movement of SprB, and of cells, was rapidly and reversibly blocked by the addition of carbonyl cyanide m-chlorophenylhydrazone, which dissipates the proton gradient across the cytoplasmic membrane. In a gliding cell, some of the SprB protein appeared to attach to the substratum. The cell body moved forward and rotated with respect to this point of attachment. Upon reaching the rear of the cell, the attached SprB often was released from the substratum, and apparently recirculated to the front of the cell along a helical path. The results suggest a model for Flavobacterium gliding, supported by mathematical analysis, in which adhesins such as SprB are propelled along a closed helical loop track, generating rotation and translation of the cell body.cell motility | proton motive force | immunofluorescence microscopy | continuous track | left-handed helix C ells of Flavobacterium johnsoniae, and of many other members of the phylum Bacteroidetes, move rapidly over surfaces at speeds of 1-3 μm/s by gliding motility (1). These cells lack flagella and pili, and the mechanism of cell movement is poorly understood. Flavobacterium gliding is thought to rely on motors embedded in the cell envelope that propel large cell-surface adhesins such as SprB and related proteins (2). Deletion of sprB results in dramatic reduction in motility. Twelve Gld proteins also are required for gliding (3

Quantum parameter estimation has many applications, from gravitational wave detection to quantum key distribution. We present the first experimental demonstration of the time-symmetric technique of quantum smoothing. We consider both adaptive and non-adaptive quantum smoothing, and show that both are better than their well-known time-asymmetric counterparts (quantum filtering). For the problem of estimating a stochastically varying phase shift on a coherent beam, our theory predicts that adaptive quantum smoothing (the best scheme) gives an estimate with a mean-square error up to 2 √ 2 times smaller than that from non-adaptive quantum filtering (the standard quantum limit). The experimentally measured improvement is 2.24 ± 0.14.PACS numbers: 42.50. Dv, 42.50.Xa, 03.65.Ta, 06.90.+v Quantum parameter estimation (QPE) is the problem of estimating an unknown classical parameter (or process) which plays a role in the preparation (or dynamics) of a quantum system [1,2], and is central to many fields including gravitational wave interferometry [5], quantum computing [3], and quantum key distribution [4]. The fundamental limit to the precision of the estimate in QPE is set by quantum mechanics [1,2]. Thus one of the key issues in QPE is the development of practical methodologies which allow measurements to approach or exceed the standard quantum limit (SQL) for a given measurement coupling [6,7,8,9,10,11,12]. Because of its wide-ranging technological relevance, the prime example of QPE is estimating an optical phase shift [13,14,15,16,17,18,19,20].Apart from some theoretical papers [19,20], work in this area of QPE has concentrated upon the problem of estimating a fixed, but unknown phase shift, which can be thought of as preparing the quantum state with an average phase equal to this parameter. It was shown theoretically [15] that for this problem adaptive homodyne measurements coupled with an optimal estimation filter can yield an estimate with mean-square error smaller than the standard quantum limit (as set by perfect heterodyne detection). This was demonstrated experimentally in Ref.[16] using very weak coherent states (for which the factor of improvement is at most 2). More recent theory and experiment have shown that interferometric measurements with photon counting can also be improved using adaptive techniques [17,18].A far richer, and in many cases more experimentally relevant, problem of quantum phase estimation arises when the phase evolves dynamically under the influence of an unknown classical stochastic process [19,20]. The general problem of estimating a classical process dynamically coupled to a quantum system under continuous measurement has recently been considered by Tsang [21], who introduced three main categories of quantum estimation: prediction or filtering, smoothing, and retrodiction. Of those, prediction or filtering is a causal estimation technique that can be used in real-time applications [24]. Smoothing and retrodiction are acausal and so cannot be used in real time, but they can be use...

Mycoplasma mobile, a parasitic bacterium lacking a peptidoglycan layer, glides on solid surfaces in the direction of a membrane protrusion at a cell pole by a unique mechanism. Recently, we proposed a working model in which cells are propelled by leg proteins clustering at the protrusion's base. The legs repeatedly catch and release sialic acids on the solid surface, a motion that is driven by the force generated by ATP hydrolysis. Here, to clarify the subcellular structure supporting the gliding force and the cell shape, we stripped the membrane by Triton X-100 and identified a unique structure, designated the ''jellyfish'' structure. In this structure, an oval solid ''bell'' Ϸ235 wide and 155 nm long is filled with a 12-nm hexagonal lattice and connected to this structure are dozens of flexible ''tentacles'' that are covered with particles of 20-nm diameter at intervals of Ϸ30 nm. The particles appear to have 180°rotational symmetry and a dimple at the center. The relation of this structure to the gliding mechanism was suggested by its cellular localization and by analyses of mutants lacking proteins essential for gliding. We identified 10 proteins as the components by mass spectrometry and found that these do not show sequence similarities with other proteins of bacterial cytoskeletons or the gliding proteins previously identified. Immunofluorescence and immunoelectron microscopy revealed that two components are localized at the bell and another that has the structure similar to the F1-ATPase ␤ subunit is localized at the tentacles.bacteria ͉ electron microscopy ͉ gliding motility ͉ immunofluorescence ͉ protein identification M ycoplasmas are commensal and occasionally parasitic bacteria with small genomes that lack a peptidoglycan layer (1). Several mycoplasma species form membrane protrusions, such as the head-like structure in Mycoplasma mobile and the attachment organelle in Mycoplasma pneumoniae (2)(3)(4)(5)(6)(7)(8)46). On solid surfaces, these species exhibit gliding motility in the direction of the protrusion; this motility is believed to be involved in the pathogenicity of mycoplasmas (3-5, 9, 10, 46). Interestingly, mycoplasmas have no surface flagella or pili, and their genomes contain no genes related to known bacterial motility. In addition, no homologs of motor proteins that are common in eukaryotic motility have been found (3-5, 11, 46). M. mobile, isolated from the gills of a freshwater fish in the early 1980s, is a fast-gliding mycoplasma (12-16). It glides smoothly and continuously on glass at an average speed of 2.0 to 4.5 m/s, or three to seven times the length of the cell per second, exerting a force of up to 27 piconewtons (pN). Recently, we identified huge proteins involved in this gliding mechanism (17-21), visualized the putative machinery and the binding protein (22,23), and identified the direct energy source used and the direct binding target (24)(25)(26). On the basis of these results, we proposed a working model in which cells are propelled by ''legs'' composed of Gli349 repeated...

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