A child of prediction. On the History, Ontology, and Computation of the Lennard-Jonesium.

The Lennard-Jones (LJ) fluid, named after mathematician-physicist-chemist Sir John Lennard-Jones (1894-1954), occupies a special place among fluids. It is an ideal entity, defined as the fluid whose particles interact according to the Lennard-Jones potential. This paper expounds the history of the LJ fluid to throw light on the tensions between theory and computational practice. The paper argues for the following claims. Firstly, the computational approach-even prior to the computer-pragmatically aims at prediction, not truth. Secondly, computer simulation methods, especially "molecular dynamics" (MD), triggered a change in epistemology. Now, simulated model fluids became targets of investigation in their own right. The urge for prediction turned the LJ fluid into the most investigated fluid in engineering thermodynamics. Thirdly, MD took a huge upswing in the 1990s, due to exploratory options in simulation. We discuss how, under these conditions, predictive success might be fraught with problems of reproducibility.

Modular Homes as a New Form of Accommodation to Tackle Homelessness: A Case Study From Cambridge, England.

In England, provision of temporary accommodation for people experiencing homelessness has often entailed using traditional construction approaches to deliver housing. However, recent experiments are using modular homes to provide temporary accommodation, accompanied by support services for people experiencing homelessness. Given the early nature of these trials, it is unclear what impacts these modular homes have on their occupants and how these projects in turn impact surrounding residents and businesses. We present a case study of the first modular homes for people experiencing homelessness in Cambridge, England, drawing on longitudinal interviews with the six residents occupying these homes. We found that the physical features of the homes, coupled with wrap-around support services, yielded positive short- and mid-term outcomes for occupants, including improved management of their substance use and money, skills development and readiness for employment, social relations, and a burgeoning sense of community, safety, and security. These positive outcomes have spurred wider interest, including the incorporation of modular homes as alternative temporary accommodation in the Homelessness and Rough Sleeping Strategy of Cambridge City Council, alongside a growing research interest in modular homes and other new schemes by the national government. We argue for further empirical studies of the impacts of different modular home projects, including those that admit more diverse resident cohorts and offer different accommodation types to establish a clear methodology for future modular homes projects in England and beyond.

Of not passing: homelessness, addiction, mental health and care during COVID-19.

People experiencing homelessness in the UK were unconditionally offered housing (and support) from the beginning of the first lockdown in March 2020. For many, that meant '(re)entering' the support system and having a chance to 'move on' to longer-term housing. This beneficial effect of some of the policy reactions to the pandemic on people experiencing homelessness was unexpected. On the flip side, however, particularly for people struggling with drug use and mental health issues, adequate support was not available for long periods of time; support was either suspended temporarily or people were excluded from institutional support for not adhering to, for instance, lockdown rules. Similarly, digital support alternatives-modelled on increasingly widespread telemedicine-did often not work specifically for people struggling with complex needs or women experiencing homelessness. This research paper reports detailed evidence of what we observed as continued and catalysed exclusions based on interviews and ethnographic observations with both people experiencing homelessness and service providers from the beginning of the COVID-19 pandemic. Referring to our insights and learnings from three locally and temporally overlapping research projects between May 2020 and April 2021, we also propose changes to redesign future (health)care provision to prevent such impasses-which extend beyond lockdown situations to general conditional housing and support.

A transformation of Bayesian statistics:Computation, prediction, and rationality.

Bayesian approaches have long been a small minority group in scientific practice, but quickly acquired a high level of popularity since the 1990s. This paper shall describe and analyze this turn. I argue that the success of Bayesian approaches hinges on computational methods that make a class of models predictive that would otherwise lack practical relevance. Philosophically, however, this orientation toward prediction comes at a price. The new computational approaches change Bayesian rationality in an important way. Namely, they undercut the interpretation of priors, turning them from an expression of beliefs held prior to new evidence into an adjustable parameter that can be manipulated flexibly by computational machinery. Thus, in the case of Bayes, one can see a coevolution of computing technology, an exploratory-iterative mode of prediction, and the conception of rationality.

Round Robin Study: Molecular Simulation of Thermodynamic Properties from Models with Internal Degrees of Freedom.

Thermodynamic properties are often modeled by classical force fields which describe the interactions on the atomistic scale. Molecular simulations are used for retrieving thermodynamic data from such models, and many simulation techniques and computer codes are available for that purpose. In the present round robin study, the following fundamental question is addressed: Will different user groups working with different simulation codes obtain coinciding results within the statistical uncertainty of their data? A set of 24 simple simulation tasks is defined and solved by five user groups working with eight molecular simulation codes: DL_POLY, GROMACS, IMC, LAMMPS, ms2, NAMD, Tinker, and TOWHEE. Each task consists of the definition of (1) a pure fluid that is described by a force field and (2) the conditions under which that property is to be determined. The fluids are four simple alkanes: ethane, propane, n-butane, and iso-butane. All force fields consider internal degrees of freedom: OPLS, TraPPE, and a modified OPLS version with bond stretching vibrations. Density and potential energy are determined as a function of temperature and pressure on a grid which is specified such that all states are liquid. The user groups worked independently and reported their results to a central instance. The full set of results was disclosed to all user groups only at the end of the study. During the study, the central instance gave only qualitative feedback. The results reveal the challenges of carrying out molecular simulations. Several iterations were needed to eliminate gross errors. For most simulation tasks, the remaining deviations between the results of the different groups are acceptable from a practical standpoint, but they are often outside of the statistical errors of the individual simulation data. However, there are also cases where the deviations are unacceptable. This study highlights similarities between computer experiments and laboratory experiments, which are both subject not only to statistical error but also to systematic error.

Disciplines, models, and computers: the path to computational quantum chemistry.

Many disciplines and scientific fields have undergone a computational turn in the past several decades. This paper analyzes this sort of turn by investigating the case of computational quantum chemistry. The main claim is that the transformation from quantum to computational quantum chemistry involved changes in three dimensions. First, on the side of instrumentation, small computers and a networked infrastructure took over the lead from centralized mainframe architecture. Second, a new conception of computational modeling became feasible and assumed a crucial role. And third, the field of computa- tional quantum chemistry became organized in a market-like fashion and this market is much bigger than the number of quantum theory experts. These claims will be substantiated by an investigation of the so-called density functional theory (DFT), the arguably pivotal theory in the turn to computational quantum chemistry around 1990.