2,488 research outputs found

    Fundamental limitations on photoisomerization from thermodynamic resource theories

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    Small, out-of-equilibrium, and quantum systems defy simple thermodynamic expressions. Such systems are exemplified by molecular switches, which exchange heat with a bath. These molecules can photoisomerize, or change conformation, or switch, upon absorbing light. The photoisomerization probability depends on kinetic details that couple the molecule's energetics to its dissipation. Therefore, a simple, general, thermodynamic-style bound on the photoisomerization probability seems out of reach. We derive such a bound using a resource theory. The resource-theory framework is a set of mathematical tools, developed in quantum information theory, used to generalize thermodynamics to small and quantum settings. From this toolkit has been derived a generalization of the second law, the thermomajorization preorder. We use thermomajorization to upper-bound the photoisomerization probability. Then, we compare the bound with an equilibrium prediction and with a Lindbladian model. We identify a realistic parameter regime in which the Lindbladian evolution saturates the thermomajorization bound. We also quantify the energy coherence in the electronic degree of freedom, and we argue that this coherence cannot promote photoisomerization. This work illustrates how quantum-information-theoretic thermodynamics can elucidate complex quantum processes in nature, experiments, and synthetics.Comment: 8.5 pages. Published versio

    Diagnosis of coronary stenosis with CT angiography comparison of automated computer diagnosis with expert readings.

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    RATIONALE AND OBJECTIVES: To compare computer-generated interpretation of coronary computed tomography angiography (cCTA) by commercially available COR Analyzer software with expert human interpretation. MATERIALS AND METHODS: This retrospective Health Insurance Portability and Accountability Act‑compliant study was approved by the institutional review board. Among 225 consecutive cCTA examinations, 207 were of adequate quality for automated evaluation. COR Analyzer interpretation was compared to human expert interpretation for detection of stenosis defined as ≥50% vessel diameter reduction in the left main, left anterior descending (LAD), circumflex (LCX), right coronary artery (RCA), or a branch vessel (diagonal, ramus, obtuse marginal, or posterior descending artery). RESULTS: Among 207 cases evaluated by COR Analyzer, human expert interpretation identified 48 patients with stenosis. COR Analyzer identified 44/48 patients (sensitivity 92%) with a specificity of 70%, a negative predictive value of 97% and a positive predictive value of 48%. COR Analyzer agreed with the expert interpretation in 75% of patients. With respect to individual segments, COR Analyzer detected 9/10 left main lesions, 33/34 LAD lesions, 14/15 LCX lesions, 27/31 RCA lesions, and 8/11 branch lesions. False-positive interpretations were localized to the left main (n = 16), LAD (n = 26), LCX (n = 21), RCA (n = 21), and branch vessels (n = 23), and were related predominantly to calcified vessels, blurred vessels, misidentification of vessels and myocardial bridges. CONCLUSIONS: Automated computer interpretation of cCTA with COR Analyzer provides high negative predictive value for the diagnosis of coronary disease in major coronary arteries as well as first-order arterial branches. False-positive automated interpretations are related to anatomic and image quality considerations

    Constructive Decision Theory

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    Contemporary approaches to decision making describe a decision problem by sets of states and outcomes, and a rich set of acts: functions from states to outcomes over which the decision maker (DM) has preferences. Real problems do not come so equipped. It is often unclear what the state and outcome spaces would be. We present an alternative foundation for decision making, in which the primitive objects of choice are syntactic programs. We show that if the DM's preference relation on objects of choice satisfies appropriate axioms, then we can find states, outcomes, and an embedding of the programs into Savage acts such that preferences can be represented by EU in the Savage framework. A modeler can test for SEU behavior without having access to the subjective states and outcomes. We illustrate the power of our approach by showing that it can represent DMs who are subject to framing effects.Decision theory, subjective expected utility, behavioral anomalies
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