arXiv subjects

Eric Smith

Publications and source records attributed to Eric Smith.

At least 37 records · Page 2Linked to original sources

arXiv2017

Charge-state distribution of Li ions from the $β$ decay of laser-trapped $^{6}$He atoms

Background: The accurate determination of atomic final states following nuclear $β$ decay plays an important role in many experiments. In particular, the charge state distributions of ions following nuclear $β$ decay are important for determinations of the $β-ν$ angular correlation with improved precision. Purpose: Our measurement aims at providing benchmarks to test theoretical calculations. Method: The kinematics of Li$^{n+}$ ions produced following the $β$ decay of $^6{\rm He}$ within an electric field were measured using $^6{\rm He}$ atoms in the metastable $(1s2s,~{^3S_1})$ and in the $(1s2p,~{^3P_2})$ states confined by a magneto-optical trap. The electron shake-off probabilities were deduced including their dependence on ion energy. Results: We find significant discrepancies on the fractions of Li ions in the different charge states with respect to a recent calculation and discuss a plausible explanation. We also point out that there is no explanation for a large discrepancy between the same calculation and a previous measurement of the Li-ion energy dependence of the charge distribution from decays of the electronic ground state.

nucl-ex↗

arXiv2017

Solving Moment Hierarchies for Chemical Reaction Networks

The study of Chemical Reaction Networks (CRN's) is a very active field. Earlier well-known results \cite{Feinberg:def_01:87, Anderson:product_dist:10} identify a topological quantity called deficiency, for any CRN, which, when exactly equal to zero, leads to a unique factorized steady-state for these networks. No results exist however for the steady states of non-zero-deficiency networks. In this paper, we show how to write the full moment-hierarchy for any non-zero-deficiency CRN obeying mass-action kinetics, in terms of equations for the factorial moments (FM). Using these, we can recursively predict values for lower moments from higher moments, reversing the procedure usually used to solve moment hierarchies. We show, for non-trivial examples, that in this manner we can predict to high accuracy, any moment of interest, for CRN's with non-zero deficiency and non-factorizable steady states.

cond-mat.stat-mech↗

arXiv2017

Flows, scaling, and the control of moment hierarchies for stochastic chemical reaction networks

Stochastic chemical reaction networks (CRNs) are complex systems which combine the features of concurrent transformation of multiple variables in each elementary reaction event, and nonlinear relations between states and their rates of change. Most general results concerning CRNs are limited to restricted cases where a topological characteristic known as deficiency takes value 0 or 1. Here we derive equations of motion for fluctuation moments at all orders for stochastic CRNs at general deficiency. We show, for the case of the mass-action rate law, that the generator of the stochastic process acts on the hierarchy of factorial moments with a finite representation. Whereas simulation of high-order moments for many-particle systems is costly, this representation reduces solution of moment hierarchies to a complexity comparable to solving a heat equation. At steady states, moment hierarchies for finite CRNs interpolate between low-order and high-order scaling regimes, which may be approximated separately by distributions similar to those for deficiency-0 networks, and connected through matched asymptotic expansions. In CRNs with multiple stable or metastable steady states, boundedness of high-order moments provides the starting condition for recursive solution downward to low-order moments, reversing the order usually used to solve moment hierarchies. A basis for a subset of network flows defined by having the same mean-regressing property as the flows in deficiency-0 networks gives the leading contribution to low-order moments in CRNs at general deficiency, in a $1/n$-expansion in large particle numbers. Our results give a physical picture of the different informational roles of mean-regressing and non-mean-regressing flows, and clarify the dynamical meaning of deficiency not only for first-moment conditions but for all orders in fluctuations.

physics.chem-ph↗

arXiv2015

On the universal structure of human lexical semantics

How universal is human conceptual structure? The way concepts are organized in the human brain may reflect distinct features of cultural, historical, and environmental background in addition to properties universal to human cognition. Semantics, or meaning expressed through language, provides direct access to the underlying conceptual structure, but meaning is notoriously difficult to measure, let alone parameterize. Here we provide an empirical measure of semantic proximity between concepts using cross-linguistic dictionaries. Across languages carefully selected from a phylogenetically and geographically stratified sample of genera, translations of words reveal cases where a particular language uses a single polysemous word to express concepts represented by distinct words in another. We use the frequency of polysemies linking two concepts as a measure of their semantic proximity, and represent the pattern of such linkages by a weighted network. This network is highly uneven and fragmented: certain concepts are far more prone to polysemy than others, and there emerge naturally interpretable clusters loosely connected to each other. Statistical analysis shows such structural properties are consistent across different language groups, largely independent of geography, environment, and literacy. It is therefore possible to conclude the conceptual structure connecting basic vocabulary studied is primarily due to universal features of human cognition and language use.

physics.soc-ph↗

arXiv2014

Polymorphic Types in ACL2

This paper describes a tool suite for the ACL2 programming language which incorporates certain ideas from the Hindley-Milner paradigm of functional programming (as exemplified in popular languages like ML and Haskell), including a "typed" style of programming with the ability to define polymorphic types. These ideas are introduced via macros into the language of ACL2, taking advantage of ACL2's guard-checking mechanism to perform type checking on both function definitions and theorems. Finally, we discuss how these macros were used to implement features of Specware, a software specification and implementation system.

cs.LO↗

arXiv2013

Metabolic evolution of a deep-branching hyperthermophilic chemoautotrophic bacterium

Aquifex aeolicus is a deep-branching hyperthermophilic chemoautotrophic bacterium restricted to hydrothermal vents and hot springs. These characteristics make it an excellent model system for studying the early evolution of metabolism. Here we present the whole-genome metabolic network of this organism and examine in detail the driving forces that have shaped it. We make extensive use of phylometabolic analysis, a method we recently introduced that generates trees of metabolic phenotypes by integrating phylogenetic and metabolic constraints. We reconstruct the evolution of a range of metabolic sub-systems, including the reductive citric acid (rTCA) cycle, as well as the biosynthesis and functional roles of several amino acids and cofactors. We show that A. aeolicus uses the reconstructed ancestral pathways within many of these sub-systems, and highlight how the evolutionary interconnections between sub-systems facilitated several key innovations. Our analyses further highlight three general classes of driving forces in metabolic evolution. One is the duplication and divergence of genes for enzymes as these progress from lower to higher substrate specificity, improving the kinetics of certain sub-systems. A second is the kinetic optimization of established pathways through fusion of enzymes, or their organization into larger complexes. The third is the minimization of the ATP unit cost to synthesize biomass, improving thermodynamic efficiency. Quantifying the distribution of these classes of innovations across metabolic sub-systems and across the tree of life will allow us to assess how a tradeoff between maximizing growth rate and growth efficiency has shaped the long-term metabolic evolution of the biosphere.

q-bio.MN↗

arXiv2012

The compositional and evolutionary logic of metabolism

Metabolism displays striking and robust regularities in the forms of modularity and hierarchy, whose composition may be compactly described. This renders metabolic architecture comprehensible as a system, and suggests the order in which layers of that system emerged. Metabolism also serves as the foundation in other hierarchies, at least up to cellular integration including bioenergetics and molecular replication, and trophic ecology. The recapitulation of patterns first seen in metabolism, in these higher levels, suggests metabolism as a source of causation or constraint on many forms of organization in the biosphere. We identify as modules widely reused subsets of chemicals, reactions, or functions, each with a conserved internal structure. At the small molecule substrate level, module boundaries are generally associated with the most complex reaction mechanisms and the most conserved enzymes. Cofactors form a structurally and functionally distinctive control layer over the small-molecule substrate. Complex cofactors are often used at module boundaries of the substrate level, while simpler ones participate in widely used reactions. Cofactor functions thus act as "keys" that incorporate classes of organic reactions within biochemistry. The same modules that organize the compositional diversity of metabolism are argued to have governed long-term evolution. Early evolution of core metabolism, especially carbon-fixation, appears to have required few innovations among a small number of conserved modules, to produce adaptations to simple biogeochemical changes of environment. We demonstrate these features of metabolism at several levels of hierarchy, beginning with the small-molecule substrate and network architecture, continuing with cofactors and key conserved reactions, and culminating in the aggregation of multiple diverse physical and biochemical processes in cells.

q-bio.MN↗

arXiv2011

Non-equilibrium phase transitions in biomolecular signal transduction

We study a mechanism for reliable switching in biomolecular signal-transduction cascades. Steady bistable states are created by system-size cooperative effects in populations of proteins, in spite of the fact that the phosphorylation-state transitions of any molecule, by means of which the switch is implemented, are highly stochastic. The emergence of switching is a nonequilibrium phase transition in an energetically driven, dissipative system described by a master equation. We use operator and functional integral methods from reaction-diffusion theory to solve for the phase structure, noise spectrum, and escape trajectories and first-passage times of a class of minimal models of switches, showing how all critical properties for switch behavior can be computed within a unified framework.

q-bio.SC↗

arXiv2011

Large-deviation principles, stochastic effective actions, path entropies, and the structure and meaning of thermodynamic descriptions

The meaning of thermodynamic descriptions is found in large-deviations scaling of the fluctuations probabilities. The primary large-deviations rate function is the entropy, which is the basis for both fluctuation theorems and for characterizing the thermodynamic interactions of systems. Freidlin-Wentzell theory provides a general formulation of large-deviations scaling for non-equilibrium stochastic processes, through a representation in terms of a Hamiltonian dynamical system. A number of related methods now exist to construct the Freidlin-Wentzell Hamiltonian for many kinds of stochastic processes; one method due to Doi and Peliti, appropriate to integer counting statistics, is widely used in reaction-diffusion theory. Using these tools together with a path-entropy method due to Jaynes, we show how to construct entropy functions that both express large-deviations scaling of fluctuations, and describe system-environment interactions, for discrete stochastic processes either at or away from equilibrium. A collection of variational methods familiar within quantum field theory, but less commonly applied to the Doi-Peliti construction, is used to define a "stochastic effective action", which is the large-deviations rate function for arbitrary non-equilibrium paths. We show how common principles of entropy maximization, applied to different ensembles of states or of histories, lead to different entropy functions and different sets of thermodynamic state variables. Yet the relations of among all these levels of description may be constructed explicitly and understood in terms of information conditions. The example systems considered introduce methods that may be used to systematically construct descriptions with all the features familiar from equilibrium thermodynamics, for a much wider range of systems describable by stochastic processes.

cond-mat.stat-mech↗

arXiv2010

A simple derivation and classification of common probability distributions based on information symmetry and measurement scale

Commonly observed patterns typically follow a few distinct families of probability distributions. Over one hundred years ago, Karl Pearson provided a systematic derivation and classification of the common continuous distributions. His approach was phenomenological: a differential equation that generated common distributions without any underlying conceptual basis for why common distributions have particular forms and what explains the familial relations. Pearson's system and its descendants remain the most popular systematic classification of probability distributions. Here, we unify the disparate forms of common distributions into a single system based on two meaningful and justifiable propositions. First, distributions follow maximum entropy subject to constraints, where maximum entropy is equivalent to minimum information. Second, different problems associate magnitude to information in different ways, an association we describe in terms of the relation between information invariance and measurement scale. Our framework relates the different continuous probability distributions through the variations in measurement scale that change each family of maximum entropy distributions into a distinct family.

math.PR↗

arXiv2010

Mapping local optical densities of states in silicon photonic structures with nanoscale electron spectroscopy

Relativistic electrons in a structured medium generate radiative losses such as Cherenkov and transition radiation that act as a virtual light source, coupling to the photonic densities of states. The effect is most pronounced when the imaginary part of the dielectric function is zero, a regime where in a non-retarded treatment no loss or coupling can occur. Maps of the resultant energy losses as a sub-5nm electron probe scans across finite waveguide structures reveal spatial distributions of optical modes in a spectral domain ranging from near-infrared to far ultraviolet.

physics.optics↗

arXiv2007

The stochastic behavior of a molecular switching circuit with feedback

Background: Using a statistical physics approach, we study the stochastic switching behavior of a model circuit of multisite phosphorylation and dephosphorylation with feedback. The circuit consists of a kinase and phosphatase acting on multiple sites of a substrate that, contingent on its modification state, catalyzes its own phosphorylation and, in a symmetric scenario, dephosphorylation. The symmetric case is viewed as a cartoon of conflicting feedback that could result from antagonistic pathways impinging on the state of a shared component. Results: Multisite phosphorylation is sufficient for bistable behavior under feedback even when catalysis is linear in substrate concentration, which is the case we consider. We compute the phase diagram, fluctuation spectrum and large-deviation properties related to switch memory within a statistical mechanics framework. Bistability occurs as either a first-order or second-order non-equilibrium phase transition, depending on the network symmetries and the ratio of phosphatase to kinase numbers. In the second-order case, the circuit never leaves the bistable regime upon increasing the number of substrate molecules at constant kinase to phosphatase ratio. Conclusions: The number of substrate molecules is a key parameter controlling both the onset of the bistable regime, fluctuation intensity, and the residence time in a switched state. The relevance of the concept of memory depends on the degree of switch symmetry, as memory presupposes information to be remembered, which is highest for equal residence times in the switched states. Reviewers: This article was reviewed by Artem Novozhilov (nominated by Eugene Koonin), Sergei Maslov, and Ned Wingreen.

q-bio.MN↗

arXiv2005

Economics: The next physical science?

We review an emerging body of work by physicists addressing questions of economic organization and function. We suggest that, beyond simply employing models familiar from physics to economic observables, remarkable regularities in economic data may suggest parts of social order that can usefully be incorporated into, and in turn can broaden, the conceptual structure of physics.

physics.soc-ph↗

arXiv2005

The thermodynamic dual structure of linear-dissipative driven systems

The spontaneous emergence of dynamical order, such as persistent currents, is sometimes argued to require principles beyond the entropy maximization of the second law of thermodynamics. I show that, for linear dissipation in the Onsager regime, current formation can be driven by exactly the Jaynesian principle of entropy maximization, suitably formulated for extended systems and nonequilibrium boundary conditions. The Legendre dual structure of equilibrium thermodynamics is also preserved, though it requires the admission of current-valued state variables, and their correct incorporation in the entropy.

physics.optics↗

arXiv2002

A quantitative model of trading and price formation in financial markets

We use standard physics techniques to model trading and price formation in a market under the assumption that order arrival and cancellations are Poisson random processes. This model makes testable predictions for the most basic properties of a market, such as the diffusion rate of prices, which is the standard measure of financial risk, and the spread and price impact functions, which are the main determinants of transaction cost. Guided by dimensional analysis, simulation, and mean field theory, we find scaling relations in terms of order flow rates. We show that even under completely random order flow the need to store supply and demand to facilitate trading induces anomalous diffusion and temporal structure in prices.

cond-mat.stat-mech↗

arXiv2002

Statistical theory of the continuous double auction

Most modern financial markets use a continuous double auction mechanism to store and match orders and facilitate trading. In this paper we develop a microscopic dynamical statistical model for the continuous double auction under the assumption of IID random order flow, and analyze it using simulation, dimensional analysis, and theoretical tools based on mean field approximations. The model makes testable predictions for basic properties of markets, such as price volatility, the depth of stored supply and demand vs. price, the bid-ask spread, the price impact function, and the time and probability of filling orders. These predictions are based on properties of order flow and the limit order book, such as share volume of market and limit orders, cancellations, typical order size, and tick size. Because these quantities can all be measured directly there are no free parameters. We show that the order size, which can be cast as a nondimensional granularity parameter, is in most cases a more significant determinant of market behavior than tick size. We also provide an explanation for the observed highly concave nature of the price impact function. On a broader level, this work suggests how stochastic models based on zero-intelligence agents may be useful to probe the structure of market institutions. Like the model of perfect rationality, a stochastic-zero intelligence model can be used to make strong predictions based on a compact set of assumptions, even if these assumptions are not fully believable.

cond-mat.stat-mech↗

arXiv2002

A model of large-scale proteome evolution

The next step in the understanding of the genome organization, after the determination of complete sequences, involves proteomics. The proteome includes the whole set of protein-protein interactions, and two recent independent studies have shown that its topology displays a number of surprising features shared by other complex networks, both natural and artificial. In order to understand the origins of this topology and its evolutionary implications, we present a simple model of proteome evolution that is able to reproduce many of the observed statistical regularities reported from the analysis of the yeast proteome. Our results suggest that the observed patterns can be explained by a process of gene duplication and diversification that would evolve proteome networks under a selection pressure, favoring robustness against failure of its individual components.

cond-mat.stat-mech↗

arXiv1992

Trivial Spectrum of Free 1+1 Light-Cone Strings

The BRST cohomology of 1+1 strings in a free light-cone gauge contains only the two-dimensional tachyon, and excludes all excited states of both matter and ghosts, including the special states that arise in the continuum conformal gauge quantization and in the $c = 1$ matrix models. This exclusion takes place at a very basic level, and therefore may signal some serious problems or at least unresolved issues involved in this gauge choice.

hep-th↗