Critical behavior of spin and chiral degrees of freedom in three-dimensional disordered XY models studied by the nonequilibrium aging method

The critical behavior of the gauge-glass and the XY spin-glass models in three dimensions is studied by analyzing their nonequilibrium aging dynamics. A new numerical method, which relies on the calculation of the two-time correlation and integrated response functions, is used to determine both the critical temperature and the nonequilibrium scaling exponents, both for spin and chiral degrees of freedom. First, the ferromagnetic XY model is studied to validate this nonequilibirum aging method (NAM), since for this nondisordered system we can compare with known results obtained with standard equilibrium and nonequilibrium techniques. When applied to the case of the gauge-glass model, we show that the NAM allows us to obtain precise and reliable values of its critical quantities, improving previous estimates. The XY spin-glass model with both Gaussian and bimodal bond distributions, is analyzed in more detail. The spin and the chiral two-time correlation and integrated response functions are calculated in our simulations. The results obtained mainly for Gaussian and, to a lesser extent, for bimodal interactions, support the existence of a spin-chiral decoupling scenario, where the chiral order occurs at a finite temperature while the spin degrees of freedom order at very low or zero temperature.Comment: 15 pages, 15 figures. Phys. Rev. B 89, 024408 (2014

Unconventional critical activated scaling of two-dimensional quantum spin-glasses

We study the critical behavior of two-dimensional short-range quantum spin glasses by numerical simulations. Using a parallel tempering algorithm, we calculate the Binder cumulant for the Ising spin glass in a transverse magnetic field with two different short-range bond distributions, the bimodal and the Gaussian ones. Through an exhaustive finite-size scaling analysis, we show that the universality class does not depend on the exact form of the bond distribution but, most important, that the quantum critical behavior is governed by an infinite randomness fixed point.Comment: 6 pages, 6 figure

Deep Remix: Remixing Musical Mixtures Using a Convolutional Deep Neural Network

Audio source separation is a difficult machine learning problem and performance is measured by comparing extracted signals with the component source signals. However, if separation is motivated by the ultimate goal of re-mixing then complete separation is not necessary and hence separation difficulty and separation quality are dependent on the nature of the re-mix. Here, we use a convolutional deep neural network (DNN), trained to estimate 'ideal' binary masks for separating voice from music, to perform re-mixing of the vocal balance by operating directly on the individual magnitude components of the musical mixture spectrogram. Our results demonstrate that small changes in vocal gain may be applied with very little distortion to the ultimate re-mix. Our method may be useful for re-mixing existing mixes

Isolating intrinsic noise sources in a stochastic genetic switch

The stochastic mutual repressor model is analysed using perturbation methods. This simple model of a gene circuit consists of two genes and three promotor states. Either of the two protein products can dimerize, forming a repressor molecule that binds to the promotor of the other gene. When the repressor is bound to a promotor, the corresponding gene is not transcribed and no protein is produced. Either one of the promotors can be repressed at any given time or both can be unrepressed, leaving three possible promotor states. This model is analysed in its bistable regime in which the deterministic limit exhibits two stable fixed points and an unstable saddle, and the case of small noise is considered. On small time scales, the stochastic process fluctuates near one of the stable fixed points, and on large time scales, a metastable transition can occur, where fluctuations drive the system past the unstable saddle to the other stable fixed point. To explore how different intrinsic noise sources affect these transitions, fluctuations in protein production and degradation are eliminated, leaving fluctuations in the promotor state as the only source of noise in the system. Perturbation methods are then used to compute the stability landscape and the distribution of transition times, or first exit time density. To understand how protein noise affects the system, small magnitude fluctuations are added back into the process, and the stability landscape is compared to that of the process without protein noise. It is found that significant differences in the random process emerge in the presence of protein noise

Maximum Principle and generalized principal eigenvalue for degenerate elliptic operators

We characterize the validity of the Maximum Principle in bounded domains for fully nonlinear degenerate elliptic operators in terms of the sign of a suitably defined generalized principal eigenvalue. Here, the maximum principle refers to the property of non-positivity of viscosity subsolutions of the Dirichlet problem. The new notion of generalized principal eigenvalue that we introduce here allows us to deal with arbitrary type of degeneracy of the elliptic operators. We further discuss the relations between this notion and other natural generalizations of the classical notion of principal eigenvalue, some of which have been previously introduced for particular classes of operators

Comorbid depressive disorders in ADHD. the role of ADHD severity, subtypes and familial psychiatric disorders

ObjectiveaaTo evaluate the presence of Major Depressive Disorder (MDD) and Dysthymic Disorder (DD) in a sample of Italian children with Attention Deficit Hyperactivity Disorder (ADHD) and to explore specific features of comorbid depressive disorders in ADHD. MethodsaaThree hundred and sixty-six consecutive, drug-naïve Caucasian Italian outpatients with ADHD were recruited and comorbid disorders were evaluated using DSM-IV-TR criteria. To evaluate ADHD severity, parents of all children filled out the ADHD Rating Scale. Thirty-seven children with comorbid MDD or DD were compared with 118 children with comorbid conduct disorder and 122 without comorbidity for age, sex, IQ level, family psychiatric history, and ADHD subtypes and severity. Resultsaa42 of the ADHD children displayed comorbid depressive disorders: 16 exhibited MDD, 21 DD, and 5 both MDD and DD. The frequency of hyperactive-impulsive subtypes was significantly lower in ADHD children with depressive disorders, than in those without any comorbidity. ADHD children with depressive disorders showed a higher number of familial psychiatric disorders and higher score in the Inattentive scale of the ADHD Rating Scale, than children without any comorbidity. No differences were found for age, sex and IQ level between the three groups. Conclusions: Consistent with previous studies in other countries, depressive disorders affect a significant proportion of ADHD children in Italy. Patient assessment and subsequent treatment should take into consideration the possible presence of this comorbidity, which could specifically increase the severity of ADHD attention problems