Monte Carlo Methods for Estimating Interfacial Free Energies and Line Tensions

Excess contributions to the free energy due to interfaces occur for many problems encountered in the statistical physics of condensed matter when coexistence between different phases is possible (e.g. wetting phenomena, nucleation, crystal growth, etc.). This article reviews two methods to estimate both interfacial free energies and line tensions by Monte Carlo simulations of simple models, (e.g. the Ising model, a symmetrical binary Lennard-Jones fluid exhibiting a miscibility gap, and a simple Lennard-Jones fluid). One method is based on thermodynamic integration. This method is useful to study flat and inclined interfaces for Ising lattices, allowing also the estimation of line tensions of three-phase contact lines, when the interfaces meet walls (where "surface fields" may act). A generalization to off-lattice systems is described as well. The second method is based on the sampling of the order parameter distribution of the system throughout the two-phase coexistence region of the model. Both the interface free energies of flat interfaces and of (spherical or cylindrical) droplets (or bubbles) can be estimated, including also systems with walls, where sphere-cap shaped wall-attached droplets occur. The curvature-dependence of the interfacial free energy is discussed, and estimates for the line tensions are compared to results from the thermodynamic integration method. Basic limitations of all these methods are critically discussed, and an outlook on other approaches is given

Critical aspects of the random-field Ising model

We investigate the critical behavior of the three-dimensional random-field Ising model (RFIM) with a Gaussian field distribution at zero temperature. By implementing a computational approach that maps the ground-state of the RFIM to the maximum-flow optimization problem of a network, we simulate large ensembles of disorder realizations of the model for a broad range of values of the disorder strength h and system sizes  = L3, with L ≤ 156. Our averaging procedure outcomes previous studies of the model, increasing the sampling of ground states by a factor of 103. Using well-established finite-size scaling schemes, the fourth-order’s Binder cumulant, and the sample-to-sample fluctuations of various thermodynamic quantities, we provide high-accuracy estimates for the critical field hc, as well as the critical exponents ν, β/ν, and γ̅/ν of the correlation length, order parameter, and disconnected susceptibility, respectively. Moreover, using properly defined noise to signal ratios, we depict the variation of the self-averaging property of the model, by crossing the phase boundary into the ordered phase. Finally, we discuss the controversial issue of the specific heat based on a scaling analysis of the bond energy, providing evidence that its critical exponent α ≈ 0−

Measurement of the splashback feature around SZ-selected Galaxy clusters with DES, SPT, and ACT

We present a detection of the splashback feature around galaxy clusters selected using the Sunyaev–Zel’dovich (SZ) signal. Recent measurements of the splashback feature around optically selected galaxy clusters have found that the splashback radius, rsp, is smaller than predicted by N-body simulations. A possible explanation for this discrepancy is that rsp inferred from the observed radial distribution of galaxies is affected by selection effects related to the optical cluster-finding algorithms. We test this possibility by measuring the splashback feature in clusters selected via the SZ effect in data from the South Pole Telescope SZ survey and the Atacama Cosmology Telescope Polarimeter survey. The measurement is accomplished by correlating these cluster samples with galaxies detected in the Dark Energy Survey Year 3 data. The SZ observable used to select clusters in this analysis is expected to have a tighter correlation with halo mass and to be more immune to projection effects and aperture-induced biases, potentially ameliorating causes of systematic error for optically selected clusters. We find that the measured rsp for SZ-selected clusters is consistent with the expectations from simulations, although the small number of SZ-selected clusters makes a precise comparison difficult. In agreement with previous work, when using optically selected redMaPPer clusters with similar mass and redshift distributions, rsp is ∼2σ smaller than in the simulations. These results motivate detailed investigations of selection biases in optically selected cluster catalogues and exploration of the splashback feature around larger samples of SZ-selected clusters. Additionally, we investigate trends in the galaxy profile and splashback feature as a function of galaxy colour, finding that blue galaxies have profiles close to a power law with no discernible splashback feature, which is consistent with them being on their first infall into the cluster

Detection of CMB-cluster lensing using polarization data from SPTpol

We report the first detection of gravitational lensing due to galaxy clusters using only the polarization of the cosmic microwave background (CMB). The lensing signal is obtained using a new estimator that extracts the lensing dipole signature from stacked images formed by rotating the cluster-centered Stokes Q U map cutouts along the direction of the locally measured background CMB polarization gradient. Using data from the SPTpol 500     deg 2 survey at the locations of roughly 18 000 clusters with richness λ ≥ 10 from the Dark Energy Survey (DES) Year-3 full galaxy cluster catalog, we detect lensing at 4.8 σ . The mean stacked mass of the selected sample is found to be ( 1.43 ± 0.40 ) × 10 14 M ⊙ which is in good agreement with optical weak lensing based estimates using DES data and CMB-lensing based estimates using SPTpol temperature data. This measurement is a key first step for cluster cosmology with future low-noise CMB surveys, like CMB-S4, for which CMB polarization will be the primary channel for cluster lensing measurements

Coexistence of both oleosin isoforms on the surface of seed oil bodies and their individual stabilization to the organelles

The oil bodies of plant seeds contain a triacylglycerol matrix surrounded by a monolayer of phospholipids embedded with alkaline proteins termed oleosins, Two distinct oleosin isoforms with molecular masses of 18 and 16 kDa are present in rice oil bodies, Chicken antibodies raised against oleosin 18 kDa and rabbit antibodies raised against oleosin 16 kDa did not cross-recognize these two homologous isoforms, This peculiar non-cross recognition was used to locate the two oleosin isoforms on the surface of oil bodies via immuno fluorescence detection using anti-chicken IgG conjugated with FITC (fluorescein isothiocyanate) and anti-rabbit IgG conjugated with Texas-Red, The results revealed that both oleosin isoforms resided on each oil body in vivo and in vitro. Artificial oil bodies were reconstituted via sonication using triacylglycerol, phospholipid, and oleosins, The results indicated that the two rice oleosin isoforms could stabilize artificial oil bodies individually whereas oleosin 16kDa provided better stability to the organelles than oleosin 18 kDa

Copacabana: A Probabilistic Membership Assignment Method for Galaxy Clusters

International audienceCosmological analyses using galaxy clusters in optical/NIR photometric surveys require robust characterization of their galaxy content. Precisely determining which galaxies belong to a cluster is crucial. In this paper, we present the COlor Probabilistic Assignment of Clusters And BAyesiaN Analysis (Copacabana) algorithm. Copacabana computes membership probabilities for {\it all} galaxies within an aperture centred on the cluster using photometric redshifts, colours, and projected radial probability density functions. We use simulations to validate Copacabana and we show that it achieves up to 89% membership accuracy with a mild dependency on photometric redshift uncertainties and choice of aperture size. We find that the precision of the photometric redshifts has the largest impact on the determination of the membership probabilities followed by the choice of the cluster aperture size. We also quantify how much these uncertainties in the membership probabilities affect the stellar mass--cluster mass scaling relation, a relation that directly impacts cosmology. Using the sum of the stellar masses weighted by membership probabilities ($\mu_{\star}$) as the observable, we find that Copacabana can reach an accuracy of 0.06 dex in the measurement of the scaling relation. These results indicate the potential of Copacabana and $\mu_{\star}$ to be used in cosmological analyses of optically selected clusters in the future

Universality aspects of the trimodal random-field Ising model

We investigate the critical properties of the d = 3 random-field Ising model with an equal-weight trimodal distribution at zero temperature. By implementing suitable graph-theoretical algorithms, we compute large ensembles of ground states for several values of the disorder strength h and system sizes up to N = 1283. Using a new approach based on the sample-to-sample fluctuations of the order parameter of the system and proper finite-size scaling techniques we estimate the critical disorder strength hc = 2.747(3) and the critical exponents of the correlation length ν = 1.34(6) and order parameter β = 0.016(4). These estimates place the model into the universality class of the corresponding Gaussian random-field Ising model