April 2013 Lunchtime Abstracts & Details

::: Individuating So-called "Indistinguishable" Quantum Systems
Adam Caulton
Cambridge University

Tuesday, April 2, 12:05 pm, 817R CL

Abstract: In this talk I investigate and build on recent heterodox proposals by Zanardi and others about the idea of a natural decomposition of an assembly. I argue that so-called "indistinguishable" quantum systems may often, in fact, be individuated---that is, picked out uniquely by some description--and may even be ascribed reduced density operators that are not all forced to become equal under permutation-invariance. Consequently, the received opinion within quantum philosophy that bosons and fermions are indiscernible---at least by their monadic properties---is mistaken.

These results also point to an alternative understanding of entanglement, which I will explain, and which coincides with one recently suggested by Ghirardi, Marinatto and Weber. I show that, according to this (better) notion, a state's being non-separable is *not* sufficient for its being entangled, so it is not the case (as is often claimed) that any fermionic state is entangled.

::: Stanford/Zollman Joint Talk

Tuesday, April 9, 12:05 pm, 817R CL

"Getting What We Pay For: Incentives, Social Structure, and the Closing of the Scientific Mind"
Kyle Stanford, Senior Visiting Fellow
University of California, Irvine

Abstract: I argue that as science has evolved from the activities of gentlemanly amateurs in the earliest scientific societies to those of the professionalized scientific communities and research universities of the 19th Century to contemporary state-sponsored academic science, the social, political, and institutional organization of scientific activity has consistently reduced the incentives offered to scientists for pursing theoretical innovation while expanding the incentives for conducting something like what Thomas Kuhn called “Normal Science” instead. Perhaps most importantly, I suggest, the shift to a system of competitive funding for specific projects awarded by peer review instituted following WWII has dramatically restricted not only the incentives but also the freedom available to scientists to pursue genuinely novel, creative, or transformative theoretical approaches. I conclude by considering potential systematic advantages and disadvantages of diversifying or at least exploring alternatives to the ways in which we presently support and incentivize scientific research.

“Understanding the reward system of science: an economic approach”
Kevin Zollman, Dept. of Philosophy
Carnegie Mellon University

Abstract: Throughout the history of science, there have been a number of different ways of rewarding scientists for their contributions to human knowledge. Utilizing an economic methodology, this paper compares these different reward systems with an eye to the systems' effects on scientists’ ability to freely choose diverse projects. This allows us to address, precisely, the often-repeated claim that the contemporary reward scheme for science stifles diversity and the free choice of scientists.

::: Minimal Models and Canonical Neural Computations
Mazviita Chirimuuta
University of Pittsburgh (HPS)

Tuesday, April 23, 12:05 pm, 817R CL

Abstract: In a recent paper, Kaplan (2011) takes up the task of extending Craver’s (2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience (i.e. research using applied mathematics and computer science to analyze and simulate neural systems). He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach to computational modeling in neuroscience is intended to replace earlier accounts which posited a level of computational analysis conceived as autonomous from underlying mechanistic details (Marr 1982).

In this talk I will discuss work in computational neuroscience that creates difficulties for Kaplan’s project. Carandini and Heeger (2012) propose that many neural response properties can be understood in terms of canonical neural computations. These are “standard computational modules that apply the same fundamental operations in a variety of contexts.” Importantly, these computations can have numerous biophysical realisations, and so straightforward examination of the mechanisms underlying these computations carries little explanatory weight. Rather than advocate a return to Marr’s system of independent levels of analysis, I propose that Carandini and Heeger’s approach should be understood as an instance of minimal modeling, comparable to that described in other branches of science (Batterman 2002).