Tort Liability and Unawareness

Unawareness is a form of bounded rationality where a person fails to conceive all feasible acts or consequences or to perceive as feasible all conceivable act-consequence links. We study the implications of unawareness for tort law, where relevant examples include the discovery of a new product or technology (new act), of a new disease or injury (new consequence), or that a product can cause an injury (new link). We argue that negligence has an important advantage over strict liability in a world with unawareness—negligence, through the stipulation of due care standards, spreads awareness about the updated probability of harm

Reverse Bayesianism and Act Independence

Karni and Vierø (2013) propose a model of belief revision under growing awareness—reverse Bayesianism—which posits that as a person becomes aware of new acts, consequences, or act-consequence links, she revises her beliefs over an expanded state space in a way that preserves the relative likelihoods of events in the original state space. A key feature of the model is that reverse Bayesianism does not fully determine the revised probability distribution. We provide an assumption—act independence—that imposes additional restrictions on reverse Bayesian belief revision. We show that with act independence knowledge of the probabilities of the new act events in the expanded state space is sufficient to fully determine the revised probability distribution in each case of growing awareness. We also explore what additional knowledge is required for reverse Bayesianism to pin down the revised probabilities without act independence

Meron-Cluster Solution of Fermion and Other Sign Problems

Numerical simulations of numerous quantum systems suffer from the notorious sign problem. Important examples include QCD and other field theories at non-zero chemical potential, at non-zero vacuum angle, or with an odd number of flavors, as well as the Hubbard model for high-temperature superconductivity and quantum antiferromagnets in an external magnetic field. In all these cases standard simulation algorithms require an exponentially large statistics in large space-time volumes and are thus impossible to use in practice. Meron-cluster algorithms realize a general strategy to solve severe sign problems but must be constructed for each individual case. They lead to a complete solution of the sign problem in several of the above cases.Comment: 15 pages,LATTICE9

Monte Carlo simulation of the classical two-dimensional one component plasma

Monte Carlo simulation, lattice dynamics in the harmonic approximation, and solution of the hypernetted chain equation were used to study the classical two-dimensional one component plasma. The system consists of a single species of charged particles immersed in a uniform neutralizing background. The particles interact via a l/r potential, where r is the two dimensional separation. Equations of state were calculated for both the liquid and solid phases. Results of calculation of the thermodynamic functions and one and two particle correlation functions are presented

Quantum disordered phase in a doped antiferromagnet

A quantitative description of the transition to a quantum disordered phase in a doped antiferromagnet is obtained with a U(1) gauge-theory, where the gap in the spin-wave spectrum determines the strength of the gauge-fields. They mediate an attractive long-range interaction whose possible bound-states correspond to charge-spin separation and pairing.Comment: 11 pages, LaTex, chris-preprint-1994-

Investigating microstructural variation in the human hippocampus using non-negative matrix factorization

In this work we use non-negative matrix factorization to identify patterns of microstructural variance in the human hippocampus. We utilize high-resolution structural and diffusion magnetic resonance imaging data from the Human Connectome Project to query hippocampus microstructure on a multivariate, voxelwise basis. Application of non-negative matrix factorization identifies spatial components (clusters of voxels sharing similar covariance patterns), as well as subject weightings (individual variance across hippocampus microstructure). By assessing the stability of spatial components as well as the accuracy of factorization, we identified 4 distinct microstructural components. Furthermore, we quantified the benefit of using multiple microstructural metrics by demonstrating that using three microstructural metrics (T1-weighted/T2-weighted signal, mean diffusivity and fractional anisotropy) produced more stable spatial components than when assessing metrics individually. Finally, we related individual subject weightings to demographic and behavioural measures using a partial least squares analysis. Through this approach we identified interpretable relationships between hippocampus microstructure and demographic and behavioural measures. Taken together, our work suggests non-negative matrix factorization as a spatially specific analytical approach for neuroimaging studies and advocates for the use of multiple metrics for data-driven component analyses

Divine Innovation: Religion and Service Provision by Religious Organizations in India

This paper examines innovations to religious and non-religious service provision by religious organizations in India. We present a stylized Hotelling-style model in which two religious organizations position themselves at opposite locations to differentiate themselves on the religious spectrum in order to compete to attract adherents. Moreover, the model predicts that economic inequality can make both organizations increase their provision of non-religious services to retain adherents. In order to test our propositions, we present unique primary survey data on the economics of religion that we have collected from 2006-2008 on 568 Hindu, Muslim, Christian, Sikh and Jain religious organizations spread across seven Indian states. We use these data to provide qualitative and descriptive statistics from the survey that is consistent and provides initial support for our propositions. We show that these organizations have substantially increased their provision of religious and non-religious services, but that there are significant variations by religion. We also provide quantitative evidence based on econometric testing to highlight that Indian religious organizations are maximizing the differences in their ideology with respect to other organizations, and are also providing higher education and health services as economic inequality increases in India