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Early poverty is associated with a cumulative load of family and community risk factors that can impact the development of self-regulatory abilities and result in socio-emotional and achievement gaps which begin early and persist across the lifespan. Ethnic minorities are disproportionately represented among children living in poverty. The longitudinal trajectories of self-regulation are important to understand in this population, in order to best inform prevention efforts. This study examines patterns of self-regulation over time among young, ethnic minority children living in low income, urban households. A stratified, random sample of 555 children, ages 2 to 4 years, (46% Black, 46% Hispanic; 47% female) were followed over three waves (including 1 and 5 year follow-ups). Internalizing and externalizing behaviors at approximately age nine were predicted by children’s early self-regulation. Latent class analyses revealed low, medium, and high levels of self-regulatory abilities at wave 1 (mean age: 2.99, SD = .81) and low and high levels, 1 year later (mean age: 4.39 (SD = .94). A gender effect was found whereby girls were more likely than boys to be in the high self-regulation class relative to the low at both waves. Using Latent Transition Analysis, distal outcomes were examined approximately 5 years after the initial assessment (mean age: 8.83, SD = .93). Children who sustained a higher level of self-regulation over time had the lowest internalizing and externalizing behaviors. Transition to low self-regulation at wave 2, regardless of initial self-regulation status, was related to greater severity of internalizing symptoms. Implications for prevention and future research are discussed. [ABSTRACT FROM AUTHOR]

Decoherence between qubits is a major bottleneck in quantum computations. Decoherence results from intrinsic quantum and thermal fluctuations as well as noise in the external fields that perform the measurement and preparation processes. With prescribed colored noise spectra for intrinsic and extrinsic noise, we present a numerical method, Quantum Accelerated Stochastic Propagator Evaluation (Q-ASPEN), to solve the time-dependent noise-averaged reduced density matrix in the presence of intrinsic and extrinsic noise. Q-ASPEN is arbitrarily accurate and can be applied to provide estimates for the resources needed to error-correct quantum computations. We employ spectral tensor trains, which combine the advantages of tensor networks and pseudospectral methods, as a variational ansatz to the quantum relaxation problem and optimize the ansatz using methods typically used to train neural networks. The spectral tensor trains in Q-ASPEN make accurate calculations with tens of quantum levels feasible. We present benchmarks for Q-ASPEN on the spin-boson model in the presence of intrinsic noise and on a quantum chain of up to 32 sites in the presence of extrinsic noise. In our benchmark, the memory cost of Q-ASPEN scales as a low-order polynomial in the size of the system once the number of system states surpasses the number of basis functions used in the spectral expansion., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

Inspired by path integral solutions to the quantum relaxation problem, we develop a numerical method to solve classical stochastic differential equations with multiplicative noise that avoids averaging over trajectories. To test the method, we simulate the dynamics of a classical oscillator multiplicatively coupled to non-Markovian noise. When accelerated using tensor factorization techniques, it accurately estimates the transition into the bifurcation regime of the oscillator and outperforms trajectory-averaging simulations with a computational cost that is orders of magnitude lower.

Measurement invariance, or the degree to which an instrument measures constructs consistently across subgroups, is critical for appropriate interpretations of measures. Given sex differences in the phenotypic and clinical presentation of autism spectrum disorder (ASD), it is particularly important to examine measurement invariance in autism instruments to ensure that ASD measures are not biased toward the more common male ASD phenotype. This study represents an important preliminary investigation evaluating the measurement equivalence of the Autism Impact Measure (AIM) across children and adolescents with ASD. The results indicated that the AIM demonstrated measurement invariance at the configural, metric, and scalar levels across sex in all five domains, including Repetitive Behavior, Communication, Atypical Behavior, Social Reciprocity, and Peer Interaction. These results suggest that ASD core symptoms assessed by the AIM were similar among male and female groups. In addition, the latent means for all five factors were not statistically significantly different across sex groups, revealing no systematic differences on any of the AIM subscales for males and females. Overall, this study showed that the AIM detects core ASD symptoms across all five areas equivalently in males and females and is not biased toward males with ASD., (© 2022 The Authors. Autism Research published by International Society for Autism Research and Wiley Periodicals LLC.)