We adapt the robust phase estimation algorithm to the evaluation of energy differences between two eigenstates using a quantum computer. This approach does not require controlled unitaries between ...auxiliary and system registers or even a single auxiliary qubit. As a proof of concept, we calculate the energies of the ground state and low-lying electronic excitations of a hydrogen molecule in a minimal basis on a cloud quantum computer. The denominative robustness of our approach is then quantified in terms of a high tolerance to coherent errors in the state preparation and measurement. Conceptually, we note that all quantum phase estimation algorithms ultimately evaluate eigenvalue differences.
A growing body of literature shows that one’s working memory (WM) capacity can be expanded through targeted training. Given the established relationship between WM and higher cognition, these ...successful training studies have led to speculation that WM training may yield broad cognitive benefits. This review considers the current state of the emerging WM training literature, and details both its successes and limitations. We identify two distinct approaches to WM training, strategy training and core training, and highlight both the theoretical and practical motivations that guide each approach. Training-related increases in WM capacity have been successfully demonstrated across a wide range of subject populations, but different training techniques seem to produce differential impacts upon the broader landscape of cognitive abilities. In particular, core WM training studies seem to produce more far-reaching transfer effects, likely because they target domain-general mechanisms of WM. The results of individual studies encourage optimism regarding the value of WM training as a tool for general cognitive enhancement. However, we discuss several limitations that should be addressed before the field endorses the value of this approach.
Delicate engineering of integrated nonlinear structures is required for developing scalable sources of non-classical light to be deployed in quantum information processing systems. In this work, we ...demonstrate a photonic molecule composed of two coupled microring resonators on an integrated nanophotonic chip, designed to generate strongly squeezed light uncontaminated by noise from unwanted parasitic nonlinear processes. By tuning the photonic molecule to selectively couple and thus hybridize only the modes involved in the unwanted processes, suppression of parasitic parametric fluorescence is accomplished. This strategy enables the use of microring resonators for the efficient generation of degenerate squeezed light: without it, simple single-resonator structures cannot avoid contamination from nonlinear noise without significantly compromising pump power efficiency. We use this device to generate 8(1) dB of broadband degenerate squeezed light on-chip, with 1.65(1) dB directly measured.
Rudolph Virchow first speculated on a relationship between inflammation and cancer more than 150 years ago. Subsequently, chronic inflammation and associated reactive free radical overload and some ...types of bacterial, viral, and parasite infections that cause inflammation were recognized as important risk factors for cancer development and account for one in four of all human cancers worldwide. Even viruses that do not directly cause inflammation can cause cancer when they act in conjunction with proinflammatory cofactors or when they initiate or promote cancer via the same signaling pathways utilized in inflammation. Whatever its origin, inflammation in the tumor microenvironment has many cancer‐promoting effects and aids in the proliferation and survival of malignant cells and promotes angiogenesis and metastasis. Mediators of inflammation such as cytokines, free radicals, prostaglandins, and growth factors can induce DNA damage in tumor suppressor genes and post‐translational modifications of proteins involved in essential cellular processes including apoptosis, DNA repair, and cell cycle checkpoints that can lead to initiation and progression of cancer.
We investigated the impact of mindfulness training (MT) on attentional performance lapses associated with task-unrelated thought (i.e., mind wandering). Periods of persistent and intensive demands ...may compromise attention and increase off-task thinking. Here, we investigated if MT may mitigate these deleterious effects and promote cognitive resilience in military cohorts enduring a high-demand interval of predeployment training. To better understand which aspects of MT programs are most beneficial, three military cohorts were examined. Two of the three groups were provided MT. One group received an 8-hour, 8-week variant of Mindfulness-based Mind Fitness Training (MMFT) emphasizing engagement in training exercises (training-focused MT, n = 40), a second group received a didactic-focused variant emphasizing content regarding stress and resilience (didactic-focused MT, n = 40), and the third group served as a no-training control (NTC, n = 24). Sustained Attention to Response Task (SART) performance was indexed in all military groups and a no-training civilian group (CIV, n = 45) before (T1) and after (T2) the MT course period. Attentional performance (measured by A', a sensitivity index) was lower in NTC vs. CIV at T2, suggesting that performance suffers after enduring a high-demand predeployment interval relative to a similar time period of civilian life. Yet, there were significantly fewer performance lapses in the military cohorts receiving MT relative to NTC, with training-focused MT outperforming didactic-focused MT at T2. From T1 to T2, A' degraded in NTC and didactic-focused MT but remained stable in training-focused MT and CIV. In sum, while protracted periods of high-demand military training may increase attentional performance lapses, practice-focused MT programs akin to training-focused MT may bolster attentional performance more than didactic-focused programs. As such, training-focused MT programs should be further examined in cohorts experiencing protracted high-demand intervals.
In the present study, a novel working memory (WM) training paradigm was used to test the malleability of WM capacity and to determine the extent to which the benefits of this training could be ...transferred to other cognitive skills. Training involved verbal and spatial versions of a complex WM span task designed to emphasize simultaneous storage and processing requirements. Participants who completed 4 weeks of WM training demonstrated significant improvements on measures of temporary memory. These WM training benefits generalized to performance on the Stroop task and, in a novel finding, promoted significant increases in reading comprehension. The results are discussed in relation to the hypothesis that WM training affects domain-general attention control mechanisms and can thereby elicit far-reaching cognitive benefits. Implications include the use of WM training as a general tool for enhancing important cognitive skills.
Growing interest in quantum computing for practical applications has led to a surge in the availability of programmable machines for executing quantum algorithms
. Present-day photonic quantum ...computers
have been limited either to non-deterministic operation, low photon numbers and rates, or fixed random gate sequences. Here we introduce a full-stack hardware-software system for executing many-photon quantum circuit operations using integrated nanophotonics: a programmable chip, operating at room temperature and interfaced with a fully automated control system. The system enables remote users to execute quantum algorithms that require up to eight modes of strongly squeezed vacuum initialized as two-mode squeezed states in single temporal modes, a fully general and programmable four-mode interferometer, and photon number-resolving readout on all outputs. Detection of multi-photon events with photon numbers and rates exceeding any previous programmable quantum optical demonstration is made possible by strong squeezing and high sampling rates. We verify the non-classicality of the device output, and use the platform to carry out proof-of-principle demonstrations of three quantum algorithms: Gaussian boson sampling, molecular vibronic spectra and graph similarity
. These demonstrations validate the platform as a launchpad for scaling photonic technologies for quantum information processing.
Abstract
We present an HST/Advanced Camera for Surveys (ACS) weak gravitational lensing analysis of 13 massive high-redshift (zmedian = 0.88) galaxy clusters discovered in the South Pole Telescope ...(SPT) Sunyaev–Zel'dovich Survey. This study is part of a larger campaign that aims to robustly calibrate mass–observable scaling relations over a wide range in redshift to enable improved cosmological constraints from the SPT cluster sample. We introduce new strategies to ensure that systematics in the lensing analysis do not degrade constraints on cluster scaling relations significantly. First, we efficiently remove cluster members from the source sample by selecting very blue galaxies in V − I colour. Our estimate of the source redshift distribution is based on Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) data, where we carefully mimic the source selection criteria of the cluster fields. We apply a statistical correction for systematic photometric redshift errors as derived from Hubble Ultra Deep Field data and verified through spatial cross-correlations. We account for the impact of lensing magnification on the source redshift distribution, finding that this is particularly relevant for shallower surveys. Finally, we account for biases in the mass modelling caused by miscentring and uncertainties in the concentration–mass relation using simulations. In combination with temperature estimates from Chandra
we constrain the normalization of the mass–temperature scaling relation ln (E(z)M500c/1014 M⊙) = A + 1.5ln (kT/7.2 keV) to $A=1.81^{+0.24}_{-0.14}(\mathrm{stat.})\,{\pm }\,0.09(\mathrm{sys.})$, consistent with self-similar redshift evolution when compared to lower redshift samples. Additionally, the lensing data constrain the average concentration of the clusters to $c_\mathrm{200c}=5.6^{+3.7}_{-1.8}$.
Abstract
We present the-wizz, an open source and user-friendly software for estimating the redshift distributions of photometric galaxies with unknown redshifts by spatially cross-correlating them ...against a reference sample with known redshifts. The main benefit of the-wizz is in separating the angular pair finding and correlation estimation from the computation of the output clustering redshifts allowing anyone to create a clustering redshift for their sample without the intervention of an ‘expert’. It allows the end user of a given survey to select any subsample of photometric galaxies with unknown redshifts, match this sample's catalogue indices into a value-added data file and produce a clustering redshift estimation for this sample in a fraction of the time it would take to run all the angular correlations needed to produce a clustering redshift. We show results with this software using photometric data from the Kilo-Degree Survey (KiDS) and spectroscopic redshifts from the Galaxy and Mass Assembly survey and the Sloan Digital Sky Survey. The results we present for KiDS are consistent with the redshift distributions used in a recent cosmic shear analysis from the survey. We also present results using a hybrid machine learning–clustering redshift analysis that enables the estimation of clustering redshifts for individual galaxies. the-wizz can be downloaded at http://github.com/morriscb/The-wiZZ/.
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