Violating the Modified Helstrom Bound with Nonprojective Measurements

We consider the discrimination of two pure quantum states with three allowed outcomes: a correct guess, an incorrect guess, and a non-guess. To find an optimum measurement procedure, we define a tunable cost that penalizes the incorrect guess and non-guess outcomes. Minimizing this cost over all projective measurements produces a rigorous cost bound that includes the usual Helstrom discrimination bound as a special case. We then show that nonprojective measurements can outperform this modified Helstrom bound for certain choices of cost function. The Ivanovic-Dieks-Peres unambiguous state discrimination protocol is recovered as a special case of this improvement. Notably, while the cost advantage of the latter protocol is destroyed with the introduction of any amount of experimental noise, other choices of cost function have optima for which nonprojective measurements robustly show an appreciable, and thus experimentally measurable, cost advantage. Such an experiment would be an unambiguous demonstration of a benefit from nonprojective measurements.Comment: 5 pages, 2 figure

Implementing generalized measurements with superconducting qubits

We describe a method to perform any generalized purity-preserving measurement of a qubit with techniques tailored to superconducting systems. First, we consider two methods for realizing a two-outcome partial projection: using a thresholded continuous measurement in the circuit QED setup, or using an indirect ancilla qubit measurement. Second, we decompose an arbitrary purity-preserving two-outcome measurement into single qubit unitary rotations and a partial projection. Third, we systematically reduce any multiple-outcome measurement to a sequence of such two-outcome measurements and unitary operations. Finally, we consider how to define suitable fidelity measures for multiple-outcome generalized measurements.Comment: 13 pages, 3 figure

PDE-Foam - a probability-density estimation method using self-adapting phase-space binning

Probability Density Estimation (PDE) is a multivariate discrimination technique based on sampling signal and background densities defined by event samples from data or Monte-Carlo (MC) simulations in a multi-dimensional phase space. In this paper, we present a modification of the PDE method that uses a self-adapting binning method to divide the multi-dimensional phase space in a finite number of hyper-rectangles (cells). The binning algorithm adjusts the size and position of a predefined number of cells inside the multi-dimensional phase space, minimising the variance of the signal and background densities inside the cells. The implementation of the binning algorithm PDE-Foam is based on the MC event-generation package Foam. We present performance results for representative examples (toy models) and discuss the dependence of the obtained results on the choice of parameters. The new PDE-Foam shows improved classification capability for small training samples and reduced classification time compared to the original PDE method based on range searching.Comment: 19 pages, 11 figures; replaced with revised version accepted for publication in NIM A and corrected typos in description of Fig. 7 and

System for Corrosion Inspection and Monitoring

This paper contains has conducted research and analysis on different corrosion identification and monitoring methods to develop an autonomous corrosion inspection system to solve the challenge issued by the University Student Design and Applied Solutions Competition. This challenge is to build an autonomous corrosion detection and monitoring system to help provide new ideas and innovations to the Department of Defense. Using research and stakeholder analysis, this research produced a system to best meet the demands of the competition and determine the best possible solution to the design challenge. Our integrated team used a systems engineering approach to produce the design that will be fielded at the competition in April 2016

Fairness Testing: Testing Software for Discrimination

This paper defines software fairness and discrimination and develops a testing-based method for measuring if and how much software discriminates, focusing on causality in discriminatory behavior. Evidence of software discrimination has been found in modern software systems that recommend criminal sentences, grant access to financial products, and determine who is allowed to participate in promotions. Our approach, Themis, generates efficient test suites to measure discrimination. Given a schema describing valid system inputs, Themis generates discrimination tests automatically and does not require an oracle. We evaluate Themis on 20 software systems, 12 of which come from prior work with explicit focus on avoiding discrimination. We find that (1) Themis is effective at discovering software discrimination, (2) state-of-the-art techniques for removing discrimination from algorithms fail in many situations, at times discriminating against as much as 98% of an input subdomain, (3) Themis optimizations are effective at producing efficient test suites for measuring discrimination, and (4) Themis is more efficient on systems that exhibit more discrimination. We thus demonstrate that fairness testing is a critical aspect of the software development cycle in domains with possible discrimination and provide initial tools for measuring software discrimination.Comment: Sainyam Galhotra, Yuriy Brun, and Alexandra Meliou. 2017. Fairness Testing: Testing Software for Discrimination. In Proceedings of 2017 11th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE), Paderborn, Germany, September 4-8, 2017 (ESEC/FSE'17). https://doi.org/10.1145/3106237.3106277, ESEC/FSE, 201

4D nanoimaging of Portland cement hydration.

Resumen de contribución al congreso "XI AUSE Conference and VI ALBA Users Meeting"Portland cements are environmentally contentious, accounting for ≈8% of the anthropogenic CO2 emissions. The understanding of the cement hydration reactions (dissolution and precipitation processes) is important to contribute to develop cements with lower CO2 footprints. We are pushing 4D (3D+time) cement hydration nanoimaging within a multiscale framework. Full-field laboratory X-ray micro Computer Tomography (μCT) is widely used to study cement hydration but the best spatial resolution is about 2 μm for a Field of View (FoV) of ≈1×2 mm (H×V) with polychromatic measurements taking hours. Moreover, the contrast between the different components is poor. Full-field propagation-based phase-contrast synchrotron X-ray μCT can study similar FoVs ≈1×2 mm with better spatial resolution, ≈0.50 μm. The monochromatic measurements are fast, i.e. 5-10 minutes. Unfortunately, the contrast is only slightly better. Cement hydration can be studied with much better contrast and spatial resolution by scanning near-field ptychographic nano-computed tomography (nCT). In this case the FoV could be ≈200×30 μm with spatial resolution, close to 250 nm, and excellent component contrast. Even air and water can be differentiated. However, these nCTs takes about 3-4 hours in optimized beamlines (BL) at third generation synchrotrons. We will present here our latest 4D nanoimaging results (Shirani et al. (2023) Nature Comm. 14:2652) from dataUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Recent Advances in Modeling Stellar Interiors

Advances in stellar interior modeling are being driven by new data from large-scale surveys and high-precision photometric and spectroscopic observations. Here we focus on single stars in normal evolutionary phases; we will not discuss the many advances in modeling star formation, interacting binaries, supernovae, or neutron stars. We review briefly: 1) updates to input physics of stellar models; 2) progress in two and three-dimensional evolution and hydrodynamic models; 3) insights from oscillation data used to infer stellar interior structure and validate model predictions (asteroseismology). We close by highlighting a few outstanding problems, e.g., the driving mechanisms for hybrid gamma Dor/delta Sct star pulsations, the cause of giant eruptions seen in luminous blue variables such as eta Car and P Cyg, and the solar abundance problem.Comment: Proceedings for invited talk at conference High Energy Density Laboratory Astrophysics 2010, Caltech, March 2010, submitted for special issue of Astrophysics and Space Science; 7 pages; 5 figure

4D nanoimaging of early age cement hydration.

Despite a century of research, our understanding of cement dissolution and precipitation processes at early ages is very limited. This is due to the lack of methods that can image these processes with enough spatial resolution, contrast and field of view. Here, we adapt near-field ptychographic nanotomography to in situ visualise the hydration of commercial Portland cement in a record-thick capillary. At 19 h, porous C-S-H gel shell, thickness of 500 nm, covers every alite grain enclosing a water gap. The spatial dissolution rate of small alite grains in the acceleration period, ∼100 nm/h, is approximately four times faster than that of large alite grains in the deceleration stage, ∼25 nm/h. Etch-pit development has also been mapped out. This work is complemented by laboratory and synchrotron microtomographies, allowing to measure the particle size distributionswith time. 4D nanoimagingwill allow mechanistically study dissolution-precipitation processes including the roles of accelerators and superplasticizers.Financial support from PID2019-104378RJ-I00 research grant, which is co-funded by FEDER, is gratefully acknowledged. ToScA (United Kingdom) is gratefully acknowledged for awarding Jim Elliott Award to Shiva Shirani, I.R.S. is thankful for funding from PTA2019-017513–I