Pair-distribution functions of two-temperature two-mass systems: Comparison of MD, HNC, CHNC, QMC and Kohn-Sham calculations for dense hydrogen

Two-temperature, two-mass quasi-equilibrium plasmas may occur in electron-ion plasmas,nuclear-matter, as well as in electron-hole condensed-matter systems. Dense two-temperature hydrogen plasmas straddle the difficult partially - degenerate regime of electron densities and temperatures which are important in astrophysics, in inertial-confinement fusion research, and other areas of warm dense matter physics. Results from Kohn-Sham calculations and QMC are used to benchmark the procedures used in classical molecular-dynamics simulations, HNC and CHNC methods to derive electron-electron and electron-proton pair - distribution functions. Then, nonequilibrium molecular dynamics for two -temperature, two-mass plasmas are used to obtain the pair distribution. Using these results, the correct HNC and CHNC procedures for the evaluation of pair-distribution functions in two-temperature two-mass two-component charged fluids are established. Results for a mass ratio of 1:5, typical of electron-hole fluids, as well as for compressed hydrogen are presented. PACS Numbers: 52.25.Kn, 52.25Gj, 71.10.-w, 52.27.Gr, 26.30.+kComment: 17 pages, four figure

Corporate Financial and Investment Policies when Future Financing is not Frictionless

Much of corporate finance is concerned with the impact of financing constraints on firms. However, the literature on financing constraints largely ignores the intertemporal implications of those constraints; in particular, how future financing constraints affect current investment decisions. We present a model in which future financing constraints lead firms to have a current preference for investments with shorter payback periods, investments with less risk, and investments that utilize more liquid/pledgeable assets. The model has a host of implications in different areas of corporate finance, including firms' capital budgeting rules, risk-taking behavior, capital structure choices, hedging strategies, and cash management policies. We show how a number of patterns reported in the empirical literature can be reconciled and interpreted in light of the intertemporal optimization problem firms solve when they face costly external financing. For example, contrary to Jensen and Meckling (1976), we show that firms may reduce rather than increase risk when leverage increases exogenously. Furthermore, firms in economies with less developed financial markets will not only take different quantities of investment, but will also take different kinds of investment (safer, short-term projects that are potentially less profitable). We also point out to several predictions that have not been empirically examined. For example, our model predicts that investment safety and liquidity are complementary: constrained firms are specially likely to distort the risk profile of their most liquid investments.

Corporate Demand for Liquidity

This paper proposes a theory of corporate liquidity demand and provides new evidence on corporate cash policies. Firms have access to valuable investment opportunities, but potentially cannot fund them with the use of external finance. Firms that are financially unconstrained can undertake all positive NPV projects regardless of their cash position, so their cash positions are irrelevant. In contrast, firms facing financial constraints have an optimal cash position determined by the value of today's investments relative to the expected value of future investments. The model predicts that constrained firms will save a positive fraction of incremental cash flows, while unconstrained firms will not. We also consider the impact of Jensen (1986) style overinvestment on the model's equilibrium, and derive conditions under which overinvestment affects corporate cash policies. We test the model's implications on a large sample of publicly-traded manufacturing firms over the 1981-2000 period, and find that firms classified as financially constrained save a positive fraction of their cash flows, while firms classified as unconstrained do not. Moreover, constrained firms save a higher fraction of cash inflows during recessions. These results are robust to the use of alternative proxies for financial constraints, and to several changes in the empirical specification. We also find weak evidence consistent with our agency-based model of corporate liquidity.

Patterns of interstate migration in the United States from the survey of income and program participation

The authors describe the Survey of Income and Program Participation (SIPP) as a data source for migration studies. The SIPP is a panel dataset that provides information on income, employment outcomes, and participation in government programs. Survey participants are interviewed for up to four years even if they move to a new household or that household migrates within the United States. This unique longitudinal design gives the survey a strong advantage over traditional data sources. The authors illustrate differences in the propensity for interstate migration among different demographic groups over the 12-year period from 1996 to 2008. They also analyze the relationship between migration choices and life-changing events, such as becoming jobless or dissolution of a marriage. Their findings suggest that future research should consider the migration choices of individuals near retirement age.Demography ; Income ; Emigration and immigration

Efficient model for electronic transport in high energy-density matter

A wide-ranging effective Boltzmann approach, originally intended for ionic transport, is applied to the computation of electronic transport coefficients without modification. Comparisons with datasets that resulted from a recent transport coefficient workshop and molecular dynamics simulations are made. While this model contains correlation information through its effective potential and strong scattering through its use of cross sections, it misses details of attractive, possibly quantum, interactions; comparisons with that dataset reveal the relative importance of these physics inputs. Through comparisons of data for electrical conductivity, thermal conductivity, temperature relaxation, and stopping power (including a new formula for the energy split due to alpha stopping), we find that the sensitivity to the missing physics is minor and often negligible. Thus, we have a single transport model that self-consistently provides all ionic and electronic transport properties in a form with negligible computational cost

Corporate Demand for Liquidity

This paper proposes a theory of corporate liquidity demand and provides new evidence on corporate cash policies. Firms have access to valuable investment opportunities, but potentially cannot fund them with the use of external finance. Firms that are financially unconstrained can undertake all positive NPV projects regardless of their cash position, so their cash positions are irrelevant. In contrast, firms facing financial constraints have an optimal cash position determined by the value of today’s investments relative to the expected value of future investments. The model predicts that constrained firms will save a positive fraction of incremental cash flows, while unconstrained firms will not. We also consider the impact of Jensen (1986) style overinvestment on the model’s equilibrium, and derive conditions under which overinvestment affects corporate cash policies. We test the model’s implications on a large sample of publicly-traded manufacturing firms over the 1981-2000 period, and find that firms classified as financially constrained save a positive fraction of their cash flows, while firms classified as unconstrained do not. Moreover, constrained firms save a higher fraction of cash inflows during recessions. These results are robust to the use of alternative proxies for financial constraints, and to several changes in the empirical specification. We also find weak evidence consistent with our agency-based model of corporate liquidity

Machine Learning Discovery of Computational Model Efficacy Boundaries

Computational models are formulated in hierarchies of variable fidelity, often with no quantitative rule for defining the fidelity boundaries. We have constructed a dataset from a wide range of atomistic computational models to reveal the accuracy boundary between higher-fidelity models and a simple, lower-fidelity model. The symbolic decision boundary is discovered by optimizing a support vector machine on the data through iterative feature engineering. This data-driven approach reveals two important results: (i) a symbolic rule emerges that is independent of the algorithm, and (ii) the symbolic rule provides a deeper understanding of the fidelity boundary. Specifically, our dataset is composed of radial distribution functions from seven high-fidelity methods that cover wide ranges in the features (element, density, and temperature); high-fidelity results are compared with a simple pair-potential model to discover the nonlinear combination of the features, and the machine learning approach directly reveals the central role of atomic physics in determining accuracy

Transport in non-ideal, multi-species plasmas

Charged particle transport plays a critical role in the evolution of high energy-density plasmas. As high-fidelity plasma models continue to incorporate new micro-physics, understanding multi-species plasma transport becomes increasingly important. We briefly outline theoretical challenges of going beyond single-component systems and binary mixtures as well as emphasize the roles experiment, simulation, theory, and modeling can play in advancing this field. The 2020 Division of Plasma Physics mini-conference on transport in Transport in Non-Ideal, Multi-Species Plasmas was organized to bring together a broad community focused on modeling plasmas with many species. This special topics issue of Physics of Plasmas touches on aspects of ion transport presented at that mini-conference. This special topics issue will provide some context for future growth in this field

Wave spectra of 2D dusty plasma solids and liquids

Brownian dynamics simulations were carried out to study wave spectra of two-dimensional dusty plasma liquids and solids for a wide range of wavelengths. The existence of a longitudinal dust thermal mode was confirmed in simulations, and a cutoff wavenumber in the transverse mode was measured. Dispersion relations, resulting from simulations, were compared with those from analytical theories, such as the random-phase approximation (RPA), quasi-localized charged approximation (QLCA), and harmonic approximation (HA). An overall good agreement between the QLCA and simulations was found for wide ranges of states and wavelengths after taking into account the direct thermal effect in the QLCA, while for the RPA and HA good agreement with simulations were found in the high and low temperature limits, respectively.Comment: 26 pages, 9 figure