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We simulate high-pressure hydrogen in its liquid phase close to molecular dissociation using a machine-learned interatomic potential. The model is trained with density functional theory (DFT) forces and energies, with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional. We show that an accurate NequIP model, an E(3)-equivariant neural network potential, accurately reproduces the phase transition present in PBE. Moreover, the computational efficiency of this model allows for substantially longer molecular dynamics trajectories, enabling us to perform a finite-size scaling (FSS) analysis to distinguish between a crossover and a true first-order phase transition. We locate the critical point of this transition, the liquid-liquid phase transition (LLPT), at 1200-1300 K and 155-160 GPa, a temperature lower than most previous estimates and close to the melting transition.

In this paper, we present HalluCana, a canary lookahead to detect and correct factuality hallucinations of Large Language Models (LLMs) in long-form generation. HalluCana detects and intervenes as soon as traces of hallucination emerge, during and even before generation. To support timely detection, we exploit the internal factuality representation in the LLM hidden space, where we investigate various proxies to the LLMs' factuality self-assessment, and discuss its relation to the models' context familiarity from their pre-training. On biography generation, our method improves generation quality by up to 2.5x, while consuming over 6 times less compute.

We present results and discuss methods for computing the melting temperature of dense molecular hydrogen using a machine learned model trained on quantum Monte Carlo data. In this newly trained model, we emphasize the importance of accurate total energies in the training. We integrate a two phase method for estimating the melting temperature with estimates from the Clausius-Clapeyron relation to provide a more accurate melting curve from the model. We make detailed predictions of the melting temperature, solid and liquid volumes, latent heat and internal energy from 50 GPa to 180 GPa for both classical hydrogen and quantum hydrogen. At pressures of roughly 173 GPa and 1635K, we observe molecular dissociation in the liquid phase. We compare with previous simulations and experimental measurements., Comment: 14 pages, 9 figures, submitted to J. Chemical Physics

Accurate knowledge of the properties of hydrogen at high compression is crucial for astrophysics (e.g. planetary and stellar interiors, brown dwarfs, atmosphere of compact stars) and laboratory experiments, including inertial confinement fusion. There exists experimental data for the equation of state, conductivity, and Thomson scattering spectra. However, the analysis of the measurements at extreme pressures and temperatures typically involves additional model assumptions, which makes it difficult to assess the accuracy of the experimental data. rigorously. On the other hand, theory and modeling have produced extensive collections of data. They originate from a very large variety of models and simulations including path integral Monte Carlo (PIMC) simulations, density functional theory (DFT), chemical models, machine-learned models, and combinations thereof. At the same time, each of these methods has fundamental limitations (fermion sign problem in PIMC, approximate exchange-correlation functionals of DFT, inconsistent interaction energy contributions in chemical models, etc.), so for some parameter ranges accurate predictions are difficult. Recently, a number of breakthroughs in first principle PIMC and DFT simulations were achieved which are discussed in this review. Here we use these results to benchmark different simulation methods. We present an update of the hydrogen phase diagram at high pressures, the expected phase transitions, and thermodynamic properties including the equation of state and momentum distribution. Furthermore, we discuss available dynamic results for warm dense hydrogen, including the conductivity, dynamic structure factor, plasmon dispersion, imaginary-time structure, and density response functions. We conclude by outlining strategies to combine different simulations to achieve accurate theoretical predictions.

Extracting structured information from unstructured text is critical for many downstream NLP applications and is traditionally achieved by closed information extraction (cIE). However, existing approaches for cIE suffer from two limitations: (i) they are often pipelines which makes them prone to error propagation, and/or (ii) they are restricted to sentence level which prevents them from capturing long-range dependencies and results in expensive inference time. We address these limitations by proposing REXEL, a highly efficient and accurate model for the joint task of document level cIE (DocIE). REXEL performs mention detection, entity typing, entity disambiguation, coreference resolution and document-level relation classification in a single forward pass to yield facts fully linked to a reference knowledge graph. It is on average 11 times faster than competitive existing approaches in a similar setting and performs competitively both when optimised for any of the individual subtasks and a variety of combinations of different joint tasks, surpassing the baselines by an average of more than 6 F1 points. The combination of speed and accuracy makes REXEL an accurate cost-efficient system for extracting structured information at web-scale. We also release an extension of the DocRED dataset to enable benchmarking of future work on DocIE, which is available at https://github.com/amazon-science/e2e-docie., Comment: Accepted at NAACL Industry Track 2024

We study the electronic excitation spectra in solid molecular hydrogen (phase I) at ambient temperature and 5-90 GPa pressures using Quantum Monte Carlo methods and Many-Body Perturbation Theory. In this range, the system changes from a wide gap molecular insulator to a semiconductor, altering the nature of the excitations from localized to delocalized. Computed gaps and spectra agree with experiments, proving the ability to predict accurately band gaps of many-body systems in presence of nuclear quantum and thermal effects., Comment: Download the archive to see the Supplemental Material

Quantum Monte Carlo (QMC) can play a very important role in generating accurate data needed for constructing potential energy surfaces. We argue that QMC has advantages in terms of a smaller systematic bias and an ability to cover phase space more completely. The stochastic noise can ease the training of the machine learning model. We discuss how stochastic errors affect the generation of effective models by analyzing the errors within a linear least squares procedure, finding that there is an advantage to having many relatively imprecise data points for constructing models. We then analyze the effect of noise on a model of many-body silicon finding that noise in some situations improves the resulting model. We then study the effect of QMC noise on two machine learning models of dense hydrogen used in a recent study of its phase diagram. The noise enable us to estimate the errors in the model. We conclude with a discussion of future research problems.

Extracting structured and grounded fact triples from raw text is a fundamental task in Information Extraction (IE). Existing IE datasets are typically collected from Wikipedia articles, using hyperlinks to link entities to the Wikidata knowledge base. However, models trained only on Wikipedia have limitations when applied to web domains, which often contain noisy text or text that does not have any factual information. We present WebIE, the first large-scale, entity-linked closed IE dataset consisting of 1.6M sentences automatically collected from the English Common Crawl corpus. WebIE also includes negative examples, i.e. sentences without fact triples, to better reflect the data on the web. We annotate ~21K triples from WebIE through crowdsourcing and introduce mWebIE, a translation of the annotated set in four other languages: French, Spanish, Portuguese, and Hindi. We evaluate the in-domain, out-of-domain, and zero-shot cross-lingual performance of generative IE models and find models trained on WebIE show better generalisability. We also propose three training strategies that use entity linking as an auxiliary task. Our experiments show that adding Entity-Linking objectives improves the faithfulness of our generative IE models., Comment: ACL 2023 Main Conference

We present a method of calculating the energy gap of a charge-neutral excitation using only ground-state calculations. We report Quantum Monte Carlo calculations of $\Gamma\rightarrow\Gamma$ and $\Gamma\rightarrow X$ particle-hole excitation energies in diamond carbon. We analyze the finite-size effect and find the same $1/L$ decay rate as that in a charged excitation, where $L$ is the linear extension of the supercell. This slow decay is attributed to the delocalized nature of the excitation in supercells too small to accommodate excitonic binding effects. At larger system sizes, the apparent $1/L$ decay crosses over to a $1/L^3$ behavior. Estimation of the scale of exciton binding can be used to correct finite-size effects of neutral gaps., Comment: 11 pages, 2 figures, 1 table

We survey the phase diagram of high-pressure molecular hydrogen with path integral molecular dynamics using a machine-learned interatomic potential trained with Quantum Monte Carlo forces and energies. Besides the HCP and C2/c-24 phases, we find two new stable phases both with molecular centers in the Fmmm-4 structure, separated by a molecular orientation transition with temperature. The high temperature isotropic Fmmm-4 phase has a reentrant melting line with a maximum at higher temperature (1450K at 150GPa) than previously estimated and crosses the liquid-liquid transition line around 1200K and 200GPa., Comment: 4 pages, 4 figures, updated acknowledgment

We introduce ReFinED, an efficient end-to-end entity linking model which uses fine-grained entity types and entity descriptions to perform linking. The model performs mention detection, fine-grained entity typing, and entity disambiguation for all mentions within a document in a single forward pass, making it more than 60 times faster than competitive existing approaches. ReFinED also surpasses state-of-the-art performance on standard entity linking datasets by an average of 3.7 F1. The model is capable of generalising to large-scale knowledge bases such as Wikidata (which has 15 times more entities than Wikipedia) and of zero-shot entity linking. The combination of speed, accuracy and scale makes ReFinED an effective and cost-efficient system for extracting entities from web-scale datasets, for which the model has been successfully deployed. Our code and pre-trained models are available at https://github.com/alexa/ReFinED, Comment: Accepted at NAACL Industry Track 2022

Recent work in entity disambiguation (ED) has typically neglected structured knowledge base (KB) facts, and instead relied on a limited subset of KB information, such as entity descriptions or types. This limits the range of contexts in which entities can be disambiguated. To allow the use of all KB facts, as well as descriptions and types, we introduce an ED model which links entities by reasoning over a symbolic knowledge base in a fully differentiable fashion. Our model surpasses state-of-the-art baselines on six well-established ED datasets by 1.3 F1 on average. By allowing access to all KB information, our model is less reliant on popularity-based entity priors, and improves performance on the challenging ShadowLink dataset (which emphasises infrequent and ambiguous entities) by 12.7 F1., Comment: Accepted at NAACL 2022

The structure of the double-layer formed at the surface of carbon electrodes is governed by the interactions between the electrode and the electrolyte species. However, carbon is notoriously difficult to simulate accurately, even with well-established methods such as electronic Density Functional Theory and Molecular Dynamics. Here we focus on the important case of a lithium ion in contact with the surface of graphite, and we perform a series of reference Quantum Monte Carlo calculations that allow us to benchmark various electronic Density Functional Theory functionals. We then fit an accurate carbon--lithium pair potential, which is used in molecular Density Functional Theory calculations to determine the free energy of the adsorption of the ion on the surface in the presence of water. The adsorption profile in solution differs markedly from the gas phase results, which emphasize the role of the solvent on the properties of the double-layer., Comment: 10 pages 4 figures

We develop a formalism to accurately account for the renormalization of electronic structure due to quantum and thermal nuclear motions within the Born-Oppenheimer approximation. We focus on the fundamental energy gap obtained from electronic addition and removal energies from Quantum Monte Carlo calculations in either the canonical or grand canonical ensembles. The formalism applies as well to effective single electron theories such as those based on Density Functional Theory. We show that electronic (Bloch) crystal momentum can be restored by marginalizing the total electron-ion wave function with respect to the nuclear equilibrium distribution, and we describe an explicit procedure to establish the band structure of electronic excitations for quantum crystals within the Born-Oppenheimer approximation. Based on the Kubo-Greenwood equation, we discuss the effects of nuclear motion on optical conductivity. Our methodology applies to the low temperature regime where nuclear motion is quantized and in general differs from the semi-classical approximation. We apply our method to study the electronic structure of C2/c-24 crystalline hydrogen at 200K and 250 GPa and discuss the optical absorption profile of hydrogen crystal at 200K and carbon diamond at 297K.

Using Quantum Monte Carlo (QMC) calculations, we investigate the insulator-metal transition observed in liquid hydrogen at high pressure. Below the critical temperature of the transition from the molecular to the atomic liquid, the fundamental electronic gap closure occurs abruptly, with a small discontinuity reflecting the weak first-order transition in the thermodynamic equation of state. Above the critical temperature, molecular dissociation sets in while the gap is still open. When the gap closes, the decay of the off-diagonal reduced density matrix shows that the liquid enters a gapless, but localized phase: there is a cross-over between the insulating and the metallic liquids. Compared to different DFT functionals, our QMC calculations provide larger values for the fundamental gap and the electronic density of states close to the band edges, indicating that optical properties from DFT potentially benefit from error cancellations.

We present Coupled Electron-Ion Monte Carlo results for the principal Hugoniot of deuterium together with an accurate study of the initial reference state of shock wave experiments. We discuss the influence of nuclear quantum effects, thermal electronic excitations, and the convergence of the energy potential surface by wave function optimization within Variational Monte Carlo and Projection Quantum Monte Carlo methods. Compared to a previous study, the new calculations also include low pressure-temperature (P,T) conditions resulting in close agreement with experimental data, while our revised results at higher (P,T) conditions still predict a more compressible Hugoniot than experimentally observed.

Non-monotonous changes in velocity autocorrelations across the transformation from molecular to atomic fluid in hydrogen under pressure are studied by ab initio molecular dynamics simulations at the temperature 2500 K. We report diffusion coefficients in a wide range of densities from purely molecular fluid up to metallic atomic fluid phase. An analysis of contributions to the velocity autocorrelation functions from the motion of molecular centers-of-mass, rotational and intramolecular vibrational modes is performed, and a crossover in the vibrational density of intramolecular modes across the transition is discussed., Comment: 7 pages, 5 figures

Real-world Relation Extraction (RE) tasks are challenging to deal with, either due to limited training data or class imbalance issues. In this work, we present Data Augmented Relation Extraction(DARE), a simple method to augment training data by properly fine-tuning GPT-2 to generate examples for specific relation types. The generated training data is then used in combination with the gold dataset to train a BERT-based RE classifier. In a series of experiments we show the advantages of our method, which leads in improvements of up to 11 F1 score points against a strong base-line. Also, DARE achieves new state of the art in three widely used biomedical RE datasets surpassing the previous best results by 4.7 F1 points on average.

We study the gap closure with pressure of crystalline molecular hydrogen. The gaps are obtained from grand-canonical Quantum Monte Carlo methods properly extended to quantum and thermal crystals, simulated by Coupled Electron Ion Monte Carlo. Nuclear zero point effects cause a large reduction in the gap ($\sim 2eV$). \CP{Depending on the structure,} the fundamental indirect gap closes \CP{between 380GPa and} 530GPa for ideal crystals and 330-380GPa for quantum crystals. Beyond this pressure the system enters into a bad metal phase where the density of states at the Fermi level increases with pressure up to $\sim$450\CP{-500} GPa when the direct gap closes. Our work partially supports the interpretation of recent experiments in high pressure hydrogen., Comment: 5 pages, 5 figures, to appear on PRL

Reasoning over paths in large scale knowledge graphs is an important problem for many applications. In this paper we discuss a simple approach to automatically build and rank paths between a source and target entity pair with learned embeddings using a knowledge base completion model (KBC). We assembled a knowledge graph by mining the available biomedical scientific literature and extracted a set of high frequency paths to use for validation. We demonstrate that our method is able to effectively rank a list of known paths between a pair of entities and also come up with plausible paths that are not present in the knowledge graph. For a given entity pair we are able to reconstruct the highest ranking path 60% of the time within the the top 10 ranked paths and achieve 49% mean average precision. Our approach is compositional since any KBC model that can produce vector representations of entities can be used., Comment: Submitted at the TextGraphs2019 Workshop at EMNLP 2019 Conference

We present a novel framework to deal with relation extraction tasks in cases where there is complete lack of supervision, either in the form of gold annotations, or relations from a knowledge base. Our approach leverages syntactic parsing and pre-trained word embeddings to extract few but precise relations,which are then used to annotate a larger cor-pus, in a manner identical to distant supervision. The resulting data set is employed to fine tune a pre-trained BERT model in order to perform relation extraction. Empirical evaluation on four data sets from the biomedical domain shows that our method significantly outperforms two simple baselines for unsupervised relation extraction and, even if not using any supervision at all, achieves slightly worse results than the state-of-the-art in three out of four data sets. Importantly, we show that it is possible to successfully fine tune a large pre-trained language model with noisy data, as op-posed to previous works that rely on gold data for fine tuning.

We develop a method for calculating the fundamental electronic gap of semiconductors and insulators using grand canonical Quantum Monte Carlo simulations. We discuss the origin of the bias introduced by supercell calculations of finite size and show how to correct the leading and subleading finite size errors either based on observables accessible in the finite-sized simulations or from DFT calculations. Our procedure is applied to solid molecular hydrogen and compared to experiment for carbon and silicon crystals., Comment: 11 pages, 5 figures; supplemental materials 21 pages

We report first principle results for nuclear structure and optical responses of high pressure liquid hydrogen along two isotherms in the region of molecular dissociation. We employ Density Functional Theory with the vdW-DF approximation (vdW) and we benchmark the results against existing predictions from Coupling Electron-Ion Monte Carlo (CEIMC). At fixed density and temperature, we find that pressure from vdW is higher than pressure from CEIMC by about 10 GPa in the molecular insulating phase and about 20 GPa in the dissociated metallic phase. Molecules are found to be overstabilized using vdW, with a slightly shorter bond length, and with a stronger resistance to compression. As a consequence, pressure dissociation along isotherms using vdW is more progressive than computed with CEIMC. Below the critical point, the liquid-liquid phase transition is observed with both theories in the same density region but the one predicted by vdW has a smaller density discontinuity, i.e. a smaller first order character. The optical conductivity computed using Kubo-Greenwood is rather similar for the two systems and reflects the slightly more pronounced molecular character of vdW., Comment: 13 pages, 7 figures, submitted to Contribution to Plasma Physics

Optical properties of compressed fluid hydrogen in the region where dissociation and metallization is observed are computed by ab-initio methods and compared to recent experimental results. We confirm that above 3000 K both processes are continuous while below 1500K the first order phase transition is accompanied by a discontinuity of the DC conductivity and the thermal conductivity, while both the reflectivity and absorption coefficient vary rapidly but continuously. Our results support the recent analysis of NIF experiments (P. Celliers et al, Science 361, 677-682 (2018)) which assigned the inception of metallization to pressures where the reflectivity is about 0.3. Our results also support the conclusion that the temperature plateau seen in laser-heated DAC experiments at temperatures higher than 1500 K corresponds to the onset of of optical absorption, not to the phase transition., Comment: 6 pages, 3 figures

The dynamic behavior of bundles of actin filaments growing against a loaded obstacle is investigated through a generalized version of the standard multi filaments Brownian Ratchet model in which the (de)polymerizing filaments are treated not as rigid rods but as semi-flexible discrete wormlike chains with a realistic value of the persistence length. By stochastic dynamic simulations we study the relaxation of a bundle of $N_f$ filaments with staggered seed arrangement against a harmonic trap load in supercritical conditions. Thanks to the time scale separation between the wall motion and the filament size relaxation, mimiking realistic conditions, this set-up allows us to extract a full load-velocity curve from a single experiment over the trap force/size range explored. We observe a systematic evolution of steady non-equilibrium states over three regimes of bundle lengths $L$. A first threshold length $\Lambda$ marks the transition between the rigid dynamic regime ($L<\Lambda$), characterized by the usual rigid filament load-velocity relationship $V(F)$, and the flexible dynamic regime ($L>\Lambda$), where the velocity $V(F,L)$ is an increasing function of the bundle length $L$ at fixed load $F$, the enhancement being the result of an improved level of work sharing among the filaments induced by flexibility. A second critical length corresponds to the beginning of an unstable regime characterized by a high probability to develop escaping filaments which start growing laterally and thus do not participate anymore to the generation of the polymerization force. This phenomenon prevents the bundle from reaching at this critical length the limit behavior corresponding to Perfect Load Sharing., Comment: 26 pages, 11 figures

We analyze in detail the electronic properties of high pressure hydrogen around the liquid-liquid phase transition based on Coupled Electron-Ion Monte Carlo calculations. Computing the off-diagonal single particle density matrix and the momentum distribution we discuss localization properties of the electrons. The abrupt changes of these distributions indicate a metal to insulator transition occurring together with the structural transition from the atomic to molecular fluid. We further discuss the electron-proton and electron-electron pair correlation functions, which also change abruptly at the transition., Comment: 10 pages, 6 figures, prepared for the proceedings of CCP2017

We present a study of the local structure of high pressure hydrogen around the liquid-liquid transition line based on results from the Coupled Electron-Ion Monte Carlo method. We report results for the Equation of State, for the radial distribution function between protons g(r) and results from a cluster analysis to detect the possible formation of stable molecular ions beyond the transition line, as well as above the critical temperature. We discuss various estimates for the molecular fraction in both phases and show that, although the presence of $H_3^+$ ions is suggested by the form of the g(r) they are not stable against thermal fluctuations., Comment: 13 pages, 7 figures, submitted to Contributions to Plasma Physics for the proceedings of SCCS2017

We performed simulations for solid molecular hydrogen at high pressures (250GPa$\leq$P$\leq$500GPa) along two isotherms at T=200 K (phases III and VI) and at T=414 K (phase IV). At T=200K we considered likely candidates for phase III, the C2c and Cmca12 structures, while at T=414K in phase IV we studied the Pc48 structure. We employed both Coupled Electron-Ion Monte Carlo (CEIMC) and Path Integral Molecular Dynamics (PIMD) based on Density Functional Theory (DFT) using the vdW-DF approximation. The comparison between the two methods allows us to address the question of the accuracy of the xc approximation of DFT for thermal and quantum protons without recurring to perturbation theories. In general, we find that atomic and molecular fluctuations in PIMD are larger than in CEIMC which suggests that the potential energy surface from vdW-DF is less structured than the one from Quantum Monte Carlo. We find qualitatively different behaviors for systems prepared in the C2c structure for increasing pressure. Within PIMD the C2c structure is dynamically partially stable for P$\leq$250GPa only: it retains the symmetry of the molecular centers but not the molecular orientation; at intermediate pressures it develops layered structures like Pbcn or Ibam and transforms to the metallic Cmca-4 structure at P$\geq$450GPa. Instead, within CEIMC, the C2c structure is found to be dynamically stable at least up to 450GPa; at increasing pressure the molecular bond length increases and the nuclear correlation decreases. For the other two structures the two methods are in qualitative agreement although quantitative differences remain. We discuss various structural properties and the electrical conductivity. We find these structures become conducting around 350GPa but the metallic Drude-like behavior is reached only at around 500GPa, consistent with recent experimental claims., Comment: 16 pages, 13 figures, invited article submitted to the special issue on Nuclear Quantum Effects in the Journal of Chemical Physics

In various cellular processes, biofilaments like F-actin and F-tubulin are able to exploit chemical energy associated to polymerization to perform mechanical work against an external load. The force-velocity relationship quantitatively summarizes the nature of this process. By a stochastic dynamical model, we give, together with the evolution of a staggered bundle of $N_f$ rigid living filaments facing a loaded wall, the corresponding force--velocity relationship. We compute systematically the simplified evolution of the model in supercritical conditions $\rho_1=U_0/W_0>1$ at $\epsilon=d^2W_0/D=0$, where $d$ is the monomer size, $D$ is the obstacle diffusion coefficient, $U_0$ and $W_0$ are the polymerization and depolymerization rates. Moreover, we see that the solution at $\epsilon=0$ is valid for a good range of small non-zero $\epsilon$ values. We consider two classical protocols: the bundle is opposed either to a constant load or to an optical trap set-up, characterized by a harmonic restoring force. The constant force case leads, for each $F$ value, to a stationary velocity $V^{stat}(F;N_f,\rho_1)$ after a relaxation with characteristic time $\tau_{micro}(F)$. When the bundle (initially taken as an assembly of filament seeds) is subjected to a harmonic restoring force (optical trap load), the bundle elongates and the load increases up to stalling (equilibrium) over a characteristic time $\tau^{OT}$. Extracted from this single experiment, the force-velocity $V^{OT}(F;N_f,\rho_1)$ curve is found to coincide with $V^{stat}(F;N_f,\rho_1)$, except at low loads. We show that this result follows from the adiabatic separation between $\tau_{micro}$ and $\tau^{OT}$, i.e. $\tau_{micro}\ll\tau^{OT}$., Comment: 19 pages, 5 figures

We establish the Statistical Mechanics framework for a bundle of Nf living and uncrosslinked actin filaments in a supercritical solution of free monomers pressing against a mobile wall. The filaments are anchored normally to a fixed planar surface at one of their ends and, because of their limited flexibility, they grow almost parallel to each other. Their growing ends hit a moving obstacle, depicted as a second planar wall, parallel to the previous one and subjected to a harmonic compressive force. The force constant is denoted as trap strength while the distance between the two walls as trap length to make contact with the experimental optical trap apparatus. For an ideal solution of reactive filaments and free monomers at fixed free monomers chemical potential, we obtain the general expression for the grand potential from which we derive averages and distributions of relevant physical quantities, namely the obstacle position, the bundle polymerization force and the number of filaments in direct contact with the wall. The grafted living filaments are modeled as discrete Wormlike chains, with Factin persistence length, subject to discrete contour length variations to model single monomer (de)polymerization steps. Rigid filaments, either isolated or in bundles, all provide average values of the stalling force in agreement with Hill's predictions, independent of the average trap length. Flexible filaments instead, for values of the trap strength suitable to prevent their lateral escape, provide an average bundle force and an average trap length slightly larger than the corresponding rigid cases (few percents). Still the stalling force remains nearly independent on the average trap length, but results from the product of two strongly L dependent contributions: the fraction of touching filaments and the single filament buckling force., Comment: 21 pages, 8 figures

Concentrating on zero temperature Quantum Monte Carlo calculations of electronic systems, we give a general description of the theory of finite size extrapolations of energies to the thermodynamic limit based on one and two-body correlation functions. We introduce new effective procedures, such as using the potential and wavefunction split-up into long and short range functions to simplify the method and we discuss how to treat backflow wavefunctions. Then we explicitly test the accuracy of our method to correct finite size errors on example hydrogen and helium many-body systems and show that the finite size bias can be drastically reduced for even small systems., Comment: 22 pages, 5 figures

We consider a single living semi-flexible filament with persistence length l_p in chemical equilibrium with a solution of free monomers at fixed monomer chemical potential mu_1 and fixed temperature T. While one end of the filament is chemically active with single monomer (de)polymerization steps, the other end is grafted normally to a rigid wall to mimick a rigid network from which the filament under consideration emerges. A second rigid wall, parallel to the grafting wall, is fixed at distance L<

We discuss the reliability of integral-equation methods based on several commonly used closure relations in determining the phase diagram of coarse-grained models of soft-matter systems characterized by mutually interacting soft and hard-core particles. Specifically, we consider a set of potentials appropriate to describe a system of hard-sphere colloids and linear homopolymers in good solvent, and investigate the behavior when the soft particles are smaller than the colloids, which is the regime of validity of the coarse-grained models. Using computer-simulation results as a benchmark, we find that the hypernetted-chain approximation provides accurate estimates of thermodynamics and structure in the colloid-gas phase in which the density of colloids is small. On the other hand, all closures considered appear to be unable to describe the behavior of the mixture in the colloid-liquid phase, as they cease to converge at polymer densities significantly smaller than those at the binodal. As a consequence, integral equations appear to be unable to predict a quantitatively correct phase diagram., Comment: 16 pages, 11 figures, 3 tables

We critically discuss and review the general ideas behind single- and multi-site coarse-grained (CG) models as applied to macromolecular solutions in the dilute and semi-dilute regime. We first consider single-site models with zero-density and density-dependent pair potentials. We highlight advantages and limitations of each option in reproducing the thermodynamic behavior and the large-scale structure of the underlying reference model. As a case study we consider solutions of linear homopolymers in a solvent of variable quality. Secondly, we extend the discussion to multi-component systems presenting, as a test case, results for mixtures of colloids and polymers. Specifically, we found the CG model with zero-density potentials to be unable to predict fluid-fluid demixing in a reasonable range of densities for mixtures of colloids and polymers of equal size. For larger colloids, the polymer volume fractions at which phase separation occurs are largely overestimated. CG models with density-dependent potentials are somewhat less accurate than models with zero-density potentials in reproducing the thermodynamics of the system and, although they presents a phase separation, they significantly underestimate the polymer volume fractions along the binodal. Finally, we discuss a general multi-site strategy, which is thermodynamically consistent and fully transferable with the number of sites, and that allows us to overcome most of the limitations discussed for single-site models., Comment: 23 pages, 9 figures, 4 tables

A coarse-graining strategy, previously developed for polymer solutions, is extended here to mixtures of linear polymers and hard-sphere colloids. In this approach groups of monomers are mapped onto a single pseudoatom (a blob) and the effective blob-blob interactions are obtained by requiring the model to reproduce some large-scale structural properties in the zero-density limit. We show that an accurate parametrization of the polymer-colloid interactions is obtained by simply introducing pair potentials between blobs and colloids. For the coarse-grained model in which polymers are modelled as four-blob chains (tetramers), the pair potentials are determined by means of the iterative Boltzmann inversion scheme, taking full-monomer pair correlation functions at zero-density as targets. For a larger number $n$ of blobs, pair potentials are determined by using a simple transferability assumption based on the polymer self-similarity. We validate the model by comparing its predictions with full-monomer results for the interfacial properties of polymer solutions in the presence of a single colloid and for thermodynamic and structural properties in the homogeneous phase at finite polymer and colloid density. The tetramer model is quite accurate for $q\lesssim 1$ ($q=\hat{R}_g/R_c$, where $\hat{R}_g$ is the zero-density polymer radius of gyration and $R_c$ is the colloid radius) and reasonably good also for $q=2$. For $q=2$ an accurate coarse-grained description is obtained by using the $n=10$ blob model. We also compare our results with those obtained by using single-blob models with state-dependent potentials., Comment: 19 pages, 8 figures, Supplementary Material 8 pages

We have performed accurate simulations of the Deuterium Hugoniot using Coupled Electron Ion Monte Carlo (CEIMC). Using highly accurate quantum Monte Carlo methods for the electrons, we study the region of maximum compression along the principal Hugoniot, where the system undergoes a continuous transition from a molecular fluid to a monatomic fluid. We include all relevant physical corrections so that a direct comparison to experiment can be made. Around 50 GPa we found a maximum compression of 4.85, roughly 10% larger than previous theoretical predictions and experimental data but still compatible with the latter because of their large uncertainty., Comment: 7 pages, 3 figures

We determine the phase diagram of mixtures of spherical colloids and neutral nonadsorbing polymers in the thermal crossover region between the $\theta$ point and the good-solvent regime. We use the generalized free-volume theory (GFVT), which turns out to be quite accurate as long as $q = R_g/R_c\lesssim 1$ ($R_g$ is the radius of gyration of the polymer and $R_c$ is the colloid radius). Close to the $\theta$ point the phase diagram is not very sensitive to solvent quality, while, close to the good-solvent region, changes of the solvent quality modify significantly the position of the critical point and of the binodals. We also analyze the phase behavior of aqueous solutions of charged colloids and polymers, using the extension of GFVT proposed by Fortini et al., J. Chem. Phys. 128, 024904 (2008).

The surface tension, the adsorption, and the depletion thickness of polymers close to a single nonadsorbing colloidal sphere are computed by means of Monte Carlo simulations. We consider polymers under good-solvent conditions and in the thermal crossover region between good-solvent and $\theta$ behavior. In the dilute regime we consider a wide range of values of $q$, from $q = 0$ (planar surface) up to $q\approx 30$-50, while in the semidilute regime, for $\rho_p/\rho_p^*\le 4$ ($\rho_p$ is the polymer concentration and $\rho_p^*$ is its value at overlap), we only consider $q = 0,0.5,1$ and 2. The results are compared with the available theoretical predictions, verifying the existing scaling arguments. Field-theoretical results, both in the dilute and in the semidilute regime, are in good agreement with the numerical estimates for polymers under good-solvent conditions., Comment: 26 pages, 12 figures

The ab-initio phase diagram of dense hydrogen is very sensitive to errors in the treatment of electronic correlation. Recently, it has been shown that the choice of the density functional has a large effect on the predicted location of both the liquid-liquid phase transition and the solid insulator-to-metal transition in dense hydrogen. To identify the most accurate functional for dense hydrogen applications, we systematically benchmark some of the most commonly used functionals using Quantum Monte Carlo. By considering several measures of functional accuracy, we conclude that the van der Waals and hybrid functionals significantly out perform LDA and PBE. We support these conclusions by analyzing the impact of functional choice on structural optimization in the molecular solid, and on the location of the liquid-liquid phase transition.

We extend our previously developed coarse-graining strategy for linear polymers with a tunable number n of effective atoms (blobs) per chain [D'Adamo et al., J. Chem. Phys. 137, 4901 (2012)] to polymer systems in thermal crossover between the good-solvent and the Theta regimes. We consider the thermal crossover in the region in which tricritical effects can be neglected, i.e. not too close to the Theta point, for a wide range of chain volume fractions Phi=c/c* (c* is the overlap concentration), up to Phi=30. Scaling crossover functions for global properties of the solution are obtained by Monte-Carlo simulations of the Domb-Joyce model. They provide the input data to develop a minimal coarse-grained model with four blobs per chain. As in the good-solvent case, the coarse-grained model potentials are derived at zero density, thus avoiding the inconsistencies related to the use of state-dependent potentials. We find that the coarse-grained model reproduces the properties of the underlying system up to some reduced density which increases when lowering the temperature towards the Theta state. Close to the lower-temperature crossover boundary, the tetramer model is accurate at least up to Phi<10, while near the good-solvent regime reasonably accurate results are obtained up to Phi<2. The density region in which the coarse-grained model is predictive can be enlarged by developing coarse-grained models with more blobs per chain. We extend the strategy used in the good-solvent case to the crossover regime. This requires a proper treatment of the length rescalings as before, but also a proper temperature redefinition as the number of blobs is increased. The case n=10 is investigated. Comparison with full-monomer results shows that the density region in which accurate predictions can be obtained is significantly wider than that corresponding to the n=4 case., Comment: 21 pages, 14 figures

Using first-principles molecular dynamics, we study the influence of nuclear quantum effects (NQEs) and nonlocal exchange--correlation density functionals (DFs) near molecular dissociation in liquid hydrogen. NQEs strongly influence intramolecular properties, such as bond stability, and are thus an essential part of the dissociation process. Moreover, by including DFs that account for either the self-interaction error or dispersion interactions, we find a much better description of molecular dissociation and metallization than previous studies based on classical protons and/or local or semi-local DFs. We obtain excellent agreement with experimentally measured optical properties along pre-compressed Hugoniots, and while we still find a first-order liquid--liquid transition at low temperatures, transition pressures are increased by more than 100 GPa.