Atomistic Monte Carlo simulation of lipid membranes

Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC) local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA) for the phospholipid dipalmitoylphosphatidylcholine (DPPC). We demonstrate rapid conformational equilibration for a single DPPC molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol

Atomistic Monte Carlo simulation of lipid membranes

Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC) local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA) for the phospholipid dipalmitoylphosphatidylcholine (DPPC). We demonstrate rapid conformational equilibration for a single DPPC molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol

IST Austria Thesis

In this Thesis, I study composite quantum impurities with variational techniques, both inspired by machine learning as well as fully analytic. I supplement this with exploration of other applications of machine learning, in particular artificial neural networks, in many-body physics. In Chapters 3 and 4, I study quasiparticle systems with variational approach. I derive a Hamiltonian describing the angulon quasiparticle in the presence of a magnetic field. I apply analytic variational treatment to this Hamiltonian. Then, I introduce a variational approach for non-additive systems, based on artificial neural networks. I exemplify this approach on the example of the polaron quasiparticle (Fröhlich Hamiltonian). In Chapter 5, I continue using artificial neural networks, albeit in a different setting. I apply artificial neural networks to detect phases from snapshots of two types physical systems. Namely, I study Monte Carlo snapshots of multilayer classical spin models as well as molecular dynamics maps of colloidal systems. The main type of networks that I use here are convolutional neural networks, known for their applicability to image data

Radio-Frequency Sensors for Detection and Analysis of Chemical and Biological Substances

Dielectric spectroscopy (DS) is an important technique for scientific and technological investigations in various areas. DS sensitivity and operating frequency ranges are critical for many applications, including lab-on-chip development where sample volumes are small with a wide range of dynamic processes to probe. In this dissertation, the design and operation considerations of radio-frequency (RF) interferometers that are based on power-dividers (PDs) and quadrature-hybrids (QHs) is presented. The effective quality factor (Qeff) of the sensor is as high as ∼3.8×10^6 with 200 μL of water samples. Such interferometers are proposed to address the sensitivity and frequency tuning challenges of current DS techniques. A high-sensitivity and stable QH-based interferometer is demonstrated by measuring glucose-water solution at a concentration level that is ten times lower than some recent RF sensors and DNA solution at ~3×10^-15 mol/mL that is close to the previously reported lowest result while the sample volume is ~1 nL. Composition analysis of ternary mixture solutions are also demonstrated with a PD-based interferometer. Using a tunable liquid attenuator by accurately changing its liquid volume, the sensitivity of a RF interferometer is tuned automatically. The obtained Qeff of the interferometer is up to 1×10^8 at ~5 GHz, i.e., ~100 times higher than previously reported results. When material-under-test, i.e., methanol-water solution in this work, is used for the tuning, a self-calibration and measurement process is demonstrated from 2 GHz to 7.5 GHz at a methanol concentration level down to 5×10^-5 mole fraction, which is 100 times lower than previously reported results. A microwave scanning technique is reported for the measurement of floating giant unilamellar vesicles (GUV) in a 25 μm wide and 18.8 μm high microfluidic channel. The measurement is conducted at 2.7 GHz and 7.9 GHz, at which a split ring resonator (SRR) operates at odd modes. A 500 nm wide and 100 μm long SRR split gap is used to scan GUVs that are slightly larger than 25 μm in diameter. The smaller fluidic channel induces flattened GUV membrane sections, which make close contact with the SRR gap surface. The used GUVs are synthesized with POPC (16:0-18:1 PC 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine), SM (16:0 Egg Sphingomyelin) and cholesterol at different molecular compositions. It is shown that SM and POPC bilayers have different dielectric permittivity values, which also change with measurement frequencies. The obtained membrane permittivity values, such as 73.64-j6.13 for POPC at 2.7 GHz, are more than 10 times larger than previously reported results. The discrepancy is likely due to the measurement of dielectric polarization responses that are parallel with, other than perpendicular to, the membrane surface. POPC and SM-rich GUV surface sections are also clearly identified from scanning measurement results. Further work is needed to enable accurate analysis of membrane composition and dynamics at high spatial resolutions

Enhancement of Self-Organisation and Adaptivity in Laser Systems

Self-organisation is an inherent mechanism in all laser systems although it is often overlooked. The self formation of spatial and spectral modes, competition between modes and much spatio-temporal dynamics are driven by the intrinsic non-linearity of saturable gain in the laser amplifier medium coupled with feedback from a resonator structure. It is highly insightful to consider the growth, extinction and competition of modes in a laser system as an evolving ecosystem with modes as species growing by stimulated emission in the gain medium, decaying by intracavity and output coupling losses, and having to compete for the common, but finite, resource of gain which is supplied by an external excitation source. The outcome of species competition is a survival-of-the-fittest that determines the final steady-state output or dynamical set of modes that can continue to persist. This thesis presents investigations into the design solid-state laser systems which utilise the inherent dynamics of optical fields and gain media in order to self-organise the system to operate in a desirable manner. The Nd:YVO4 bounce geometry laser amplifier is employed throughout this thesis. A numerical investigation of the thermally induced lensing within the laser crystal is reported. Optimisation of the geometry parameters is explored as well as investigation into future developments, such as the utilisation of an additional sapphire crystal to directly cool the laser crystal pump face. This is shown to theoretically reduce the horizontal thermally induced lens strengths by a factor of 4. Single longitudinal mode single longitudinal mode (SLM) ring lasers where the unidirectionality is imposed either by an extra-cavity ‘parasitic’ pass of the gain media or by retro-reflection of one of the two outputs are investigated. SLM TEM00 output powers of up to 20W are demonstrated without the need for a Faraday isolator. A self-adaptive sensor which allows the measurement of remote surface vibrations is demonstrated. The two-wave mixing interaction within a saturable gain media is shown to allow measurement of high frequency phase modulations (>10kHz) whilst adapting to cancel out low frequency perturbations. This sensor system is shown to have potential as a remote ultrasound detector as the holographic nature allows high frequency measurement of the vibrations of rough remote surfaces. Self-starting self-adaptive lasers, where a four wave mixing interaction within the saturable gain medium is utilised to generate phase conjugate and aberration corrective laser systems are experimentally investigated. This work is extended to show that the gain hologram is capable of adapting to low frequency phase modulations in order to maintain a high quality output. A demonstration of self-organised coherent beam combination of two bounce geometry laser oscillators into a single output beam is reported. A combined output beam of 35.7W was demonstrated from 94W of pump power. This coherent beam combination is extended into the technique of phase conjugate self-organised coherent beam combination (PCSOCBC) where a first demonstration of the combination of two self-starting self-adaptive modules is reported. It is shown that the adaptive modules allow efficient beam combination (94%) with a combined output of 27W. As the self-starting self-adaptive modules do not have predefined spatial or spectral modes it is believed that this system could be scaled to much higher numbers of modules than is possible with conventional self-organised coherent beam combination

Structural Organization and Chemical Activity Revealed by New Developments in Single-Molecule Fluorescence and Orientation Imaging

Single-molecule (SM) fluorescence and its localization are important and versatile tools for understanding and quantifying dynamical nanoscale behavior of nanoparticles and biological systems. By actively controlling the concentration of fluorescent molecules and precisely localizing individual single molecules, it is possible to overcome the classical diffraction limit and achieve \u27super-resolution\u27 with image resolution on the order of 10 nanometers. Single molecules also can be considered as nanoscale sensors since their fluorescence changes in response to their local nanoenvironment. This dissertation discusses extending this SM approach to resolve heterogeneity and dynamics of nanoscale materials and biophysical structures by using positions and orientations of single fluorescent molecules. I first present an SM approach for resolving spatial variations in the catalytic activity of individual photocatalysts. Quantitative colocalization of chemically triggered molecular probes reveals the role of structural defects on the activity of catalytic nanoparticles. Next, I demonstrate a new engineered optical point spread function (PSF), called the Duo-spot PSF, for SM orientation measurements. This PSF exhibits high sensitivity for estimating orientations of dim fluorescent molecules. This dissertation also discusses a new amyloid imaging method, transient amyloid binding (TAB) microscopy, for studying heterogeneous organization of amyloid structures, which are associated with various aging-related neurodegenerative diseases. Continuous transient binding of dye molecules to amyloid structures generates photon bursts for SM localization over hours to days with minimal photobleaching, yielding about 40% more localizations than standard immunolabeling. Finally, I augment TAB imaging to simultaneously measure positions and orientations of fluorescent molecules bound to amyloid surfaces. This new method, termed single-molecule orientation localization microscopy (SMOLM), robustly and sensitively measures the in-plane (xy) orientations of fluorophores (approximately 9 degree precision in azimuthal angle) near a refractive index interface and reveals structural heterogeneities along amyloid fibrillar networks that cannot be resolved by SM localization alone

Sequence Determinants of the Individual and Collective Behaviour of Intrinsically Disordered Proteins

Intrinsically disordered proteins and protein regions (IDPs) represent around thirty percent of the eukaryotic proteome. IDPs do not fold into a set three dimensional structure, but instead exist in an ensemble of inter-converting states. Despite being disordered, IDPs are decidedly not random; well-defined - albeit transient - local and long-range interactions give rise to an ensemble with distinct statistical biases over many length-scales. Among a variety of cellular roles, IDPs drive and modulate the formation of phase separated intracellular condensates, non-stoichiometric assemblies of protein and nucleic acid that serve many functions. In this work, we have explored how the amino acid sequence of IDPs determines their conformational behaviour, and how sequence and single chain behaviour influence their collective behaviour in the context of phase separation. In part I, in a series of studies, we used simulation, theory, and statistical analysis coupled with a wide range of experimental approaches to uncover novel rules that further explore how primary sequence and local structure influence the global and local behaviour of disordered proteins, with direct implications for protein function and evolution. We found that amino acid sidechains counteract the intrinsic collapse of the peptide backbone, priming the backbone for interaction and providing a fully reconciliatory explanation for the mechanism of action associated with the denaturants urea and GdmCl. We discovered that proline can engender a conformational buffering effect in IDPs to counteract standard electrostatic effects, and that the patterning those proline residues can be a crucial determinant of the conformational ensemble. We developed a series of tools for analysing primary sequences on a proteome wide scale and used them to discover that different organisms can have substantially different average sequence properties. Finally, we determined that for the normally folded protein NTL9, the unfolded state under folding conditions is relatively expanded but has well defined native and non-native structural preferences. In part II, we identified a novel mode of phase separation in biology, and explored how this could be tuned through sequence design. We discovered that phase separated liquids can be many orders of magnitude more dilute than simple mean-field theories would predict, and developed an analytic framework to explain and understand this phenomenon. Finally, we designed, developed and implemented a novel lattice-based simulation engine (PIMMS) to provide sequence-specific insight into the determinants of conformational behaviour and phase separation. PIMMS allows us to accurately and rapidly generate sequence-specific conformational ensembles and run simulations of hundreds of polymers with the goal of allowing us to systematically elucidate the link between primary sequence of phase separation

Exotic Ground States and Dynamics in Constrained Systems

The overarching theme of this thesis is the question of how constraints influence collective behavior. Constraints are crucial in shaping both static and dynamic properties of systems across diverse areas within condensed matter physics and beyond. For example, the simple geometric constraint that hard particles cannot overlap at high density leads to slow dynamics and jamming in glass formers. Constraints also arise effectively at low temperature as a consequence of strong competing interactions in magnetic materials, where they give rise to emergent gauge theories and unconventional magnetic order. Enforcing constraints artificially in turn can be used to protect otherwise fragile quantum information from external noise. This thesis in particular contains progress on the realization of different unconventional phases of matter in constrained systems. The presentation of individual results is organized by the stage of realization of the respective phase. Novel physical phenomena after conceptualization are often exemplified in simple, heuristic models bearing little resemblance of actual matter, but which are interesting enough to motivate efforts with the final goal of realizing them in some way in the lab. One form of progress is then to devise refined models, which retain a degree of simplification while still realizing the same physics and improving the degree of realism in some direction. Finally, direct efforts in realizing either the original models or some refined version in experiment today are mostly two-fold. One route, having grown in importance rapidly during the last two decades, is via the engineering of artificial systems realizing suitable models. The other, more conventional way is to search for realizations of novel phases in materials. The thesis is divided into three parts, where Part I is devoted to the study of two simple models, while artificial systems and real materials are the subject of Part II and Part III respectively. Below, the content of each part is summarized in more detail. After a general introduction to entropic ordering and slow dynamics we present a family of models devised as a lattice analog of hard spheres. These are often studied to explore whether low-dimensional analogues of mean-field glass- and jamming transitions exist, but also serve as the canonical model systems for slow dynamics in granular materials more generally. Arguably the models in this family do not offer a close resemblance of actual granular materials. However, by studying their behavior far from equilibrium, we observe the onset of slow dynamics and a kinetic arrest for which, importantly, we obtain an essentially complete analytical and numerical understanding. Particularly interesting is the fact that this understanding hinges on the (in-)ability to anneal topological defects in the presence of a hardcore constraints, which resonates with some previous proposals for an understanding of the glass transition. As another example of anomalous dynamics arising in a magnetic system, we also present a detailed study of a two-dimensional fracton spin liquid. The model is an Ising system with an energy function designed to give rise to an emergent higher-rank gauge theory at low energy. We show explicitly that the number of zero-energy states in the model scales exponentially with the system size, establishing a finite residual entropy. A purpose-built cluster Monte-Carlo algorithm makes it possible to study the behavior of the model as a function of temperature. We show evidence for a first order transition from a high-temperature paramagnet to a low-temperature phase where correlations match predictions of a higher-rank coulomb phase. Turning away from heuristic models, the second part of the thesis begins with an introduction to quantum error correction, a scheme where constraints are artificially imposed in a quantum system through measurement and feedback. This is done in order to preserve quantum information in the presence of external noise, and is widely believed to be necessary in order to one day harness the full power of quantum computers. Given a certain error-correcting code as well as a noise model, a particularly interesting quantity is the threshold of the code, that is the critical amount of external noise below which quantum error correction becomes possible. For the toric code under independent bit- and phase-flip noise for example, the threshold is well known to map to the paramagnet to ferromagnet transition of the two-dimensional random-bond Ising model along the Nishimori line. Here, we present the first generalization of this mapping to a family of codes with finite rate, that is a family where the number of encoded logical qubits grows linearly with the number of physical qubits. In particular, we show that the threshold of hyperbolic surface codes maps to a paramagnet to ferromagnet transition in what we call the 'dual'' random-bond Ising model on regular tessellations of compact hyperbolic manifolds. This model is related to the usual random-bond Ising model by the Kramers-Wannier duality but distinct from it even on self-dual tessellations. As a corollary, we clarify long-standing issues regarding self-duality of the Ising model in hyperbolic space. The final part of the thesis is devoted to the study of material candidates of quantum spin ice, a three-dimensional quantum spin liquid. The work presented here was done in close collaboration with experiment and focuses on a particular family of materials called dipolar-octupolar pyrochlores. This family of materials is particularly interesting because they might realize novel exotic quantum states such as octupolar spin liquids, while at the same time being described by a relatively simple model Hamiltonian. This thesis contains a detailed study of ground state selection in dipolar-octupolar pyrochlore magnets and its signatures as observable in neutron scattering. First, we present evidence that the two compounds Ce2Zr2O7 and Ce2Sn2O7 despite their similar chemical composition realize an exotic quantum spin liquid state and an ordered state respectively. Then, we also study the ground-state selection in dipolar-octupolar pyrochlores in a magnetic field. Most importantly, we show that the well-known effective one-dimensional physics -- arising when the field is applied along a certain crystallographic axis -- is expected to be stable at experimentally relevant temperatures. Finally, we make predictions for neutron scattering in the large-field phase and compare these to measurements on Ce2Zr2O7

Clustering Arabic Tweets for Sentiment Analysis

The focus of this study is to evaluate the impact of linguistic preprocessing and similarity functions for clustering Arabic Twitter tweets. The experiments apply an optimized version of the standard K-Means algorithm to assign tweets into positive and negative categories. The results show that root-based stemming has a significant advantage over light stemming in all settings. The Averaged Kullback-Leibler Divergence similarity function clearly outperforms the Cosine, Pearson Correlation, Jaccard Coefficient and Euclidean functions. The combination of the Averaged Kullback-Leibler Divergence and root-based stemming achieved the highest purity of 0.764 while the second-best purity was 0.719. These results are of importance as it is contrary to normal-sized documents where, in many information retrieval applications, light stemming performs better than root-based stemming and the Cosine function is commonly used