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We present a machine learning-based anomaly detection product, AI Detect and Respond (AIDR), that monitors Walmart's business and system health in real-time. During the validation over 3 months, the product served predictions from over 3000 models to more than 25 application, platform, and operation teams, covering 63\% of major incidents and reducing the mean-time-to-detect (MTTD) by more than 7 minutes. Unlike previous anomaly detection methods, our solution leverages statistical, ML and deep learning models while continuing to incorporate rule-based static thresholds to incorporate domain-specific knowledge. Both univariate and multivariate ML models are deployed and maintained through distributed services for scalability and high availability. AIDR has a feedback loop that assesses model quality with a combination of drift detection algorithms and customer feedback. It also offers self-onboarding capabilities and customizability. AIDR has achieved success with various internal teams with lower time to detection and fewer false positives than previous methods. As we move forward, we aim to expand incident coverage and prevention, reduce noise, and integrate further with root cause recommendation (RCR) to enable an end-to-end AIDR experience., Comment: ASPLOS 2024 AIOps workshop

Neutrinos can acquire both dynamic and geometric phases due to the non-trivial mixing between mass and flavour eigenstates. In this article, we derive the general expressions for all plausible gauge invariant diagonal and off-diagonal geometric phases in the three flavour neutrino model using the kinematic approach. We find that diagonal and higher order off-diagonal geometric phases are sensitive to the mass ordering and the Dirac CP violating phase $\delta$. We show that, third order off-diagonal geometric phase ($\Phi_{\mu e\tau}$) is invariant under any cyclic or non-cyclic permutations of flavour indices when the Dirac CP phase is zero. For non-zero $\delta$, we find that $\Phi_{\mu e\tau}(\delta)=\Phi_{e \mu \tau}(-\delta)$. Further, we explore the effects of matter background using a two flavour neutrino model and show that the diagonal geometric phase is either 0 or $\pi$ in the MSW resonance region and takes non-trivial values elsewhere. The transition between zero and $\pi$ occurs at the point of complete oscillation inversion called the nodal point, where the diagonal geometric phase is not defined. Also, in two flavour approximations, two distinct diagonal geometric phases are co-functions with respect to the mixing angle. Finally, in the two flavour model, we show that the only second order off-diagonal geometric phase is a topological invariant quantity and is always $\pi$., Comment: 12 pages, accepted for publication in Modern Physics Letters A, similar to the accepted version, different from arXiv:2104.12632

The Pancharatnam - Berry phase (PBP) of purely geometric origin appears as a reparametrization invariant quantity of ray Space. In this article, we investigate the properties exhibited by PBP in neutrino mixing. We map the neutrino flavour modes to independent flavour vacuum states and compute PBP using Bargmann invariant. We derive the exact formula for PBP in two flavour approximation using the kinematic approach. Our result reproduces previous results of Blasone et al. under cyclic condition. Inspired by the work of Mukunda and Simon, we investigate the total and dynamical phases separately. This method leads us to identify the existence of nodal points in the mixing parameter space. At nodal points, PBP changes by a value $\pi$, and it originates from the total phase. We report the direct relation between nodal points and MSW resonance, giving physical meaning to nodal points. Our analysis shows the ability of PBP to differentiate between different mass hierarchies and set numerical bounds to $\Delta m^2$ by changing total energy. We extend our studies to three flavour model and found that PBP is sensitive to the Dirac $CP$ phase ($\delta_{CP}$). Using our $N$-qubit architecture of the $N$-flavour neutrino model, one can immediately study the dynamical characteristics like mode entanglement between neutrino flavour modes., Comment: 14 pages, 14 figures (including subfigures)

We study the effect of Kerr type nonlinear medium in quantum state transfer. We have investigated the effect of different coupling schemes and Kerr medium parameters $p$ and $\omega_{{K}}$. We found that, the Kerr medium introduced in the connection channel can act like a controller for quantum state transfer. The numerical simulations are performed without taking the adiabatic approximation. Rotating wave approximation is used in the atom-cavity interaction only in the lower coupling regime., Comment: 11 pages

We study two coupled cavities with a single two-level system in each and a second-order non-linear process in one of the cavities. Introduction of a harmonic time dependence on the non-linear coupling is utilized for the preservation of dynamics. It is observed that, even though the preservation period is independent of the initial state, the preserved dynamics depends on the initial state. We calculated the von Neumann entropy and mutual information to study the entanglement present between the subsystems. From which it is found that the time-dependent coupling also preserves the entanglement produced in the system., Comment: 21 pages, 11 figures

The exact period determination of a multi-periodic variable star based on its luminosity time series data is believed a task requiring skill and experience. Thus the majority of available time series analysis techniques require human intervention to some extent. The present work is dedicated to establish an automated method of period (or frequency) determination from the time series database of variable stars. Relying on the SigSpec method (Reegen 2007), the technique established here employs a statistically unbiased treatment of frequency-domain noise and avoids spurious (i. e. noise induced) and alias peaks to the highest possible extent. Several add-on's were incorporated to tailor SigSpec to our requirements. We present tests on 386 stars taken from ASAS2 project database. From the output file produced by SigSpec, the frequency with maximum spectral significance is chosen as the genuine frequency. Out of 386 variable stars available in the ASAS2 database, our results contain 243 periods recovered exactly and also 88 half periods, 42 different periods etc. SigSpec has the potential to be effectively used for fully automated period detection from variable stars' time series database. The exact detection of periods helps us to identify the type of variability and classify the variable stars, which provides a crucial information on the physical processes effective in stellar atmospheres., Comment: 7 pages, 3 figures, 4 tables, submitted to A&A

The Call admission control (CAC) is one of the Radio Resource Management (RRM) techniques plays instrumental role in ensuring the desired Quality of Service (QoS) to the users working on different applications which have diversified nature of QoS requirements. This paper proposes a fuzzy neural approach for call admission control in a multi class traffic based Next Generation Wireless Networks (NGWN). The proposed Fuzzy Neural Call Admission Control (FNCAC) scheme is an integrated CAC module that combines the linguistic control capabilities of the fuzzy logic controller and the learning capabilities of the neural networks .The model is based on Recurrent Radial Basis Function Networks (RRBFN) which have better learning and adaptability that can be used to develop the intelligent system to handle the incoming traffic in the heterogeneous network environment. The proposed FNCAC can achieve reduced call blocking probability keeping the resource utilisation at an optimal level. In the proposed algorithm we have considered three classes of traffic having different QoS requirements. We have considered the heterogeneous network environment which can effectively handle this traffic. The traffic classes taken for the study are Conversational traffic, Interactive traffic and back ground traffic which are with varied QoS parameters. The paper also presents the analytical model for the CAC .The paper compares the call blocking probabilities for all the three types of traffic in both the models. The simulation results indicate that compared to Fuzzy logic based CAC, Conventional CAC, The simulation results are optimistic and indicates that the proposed FNCAC algorithm performs better where the call blocking probability is minimal when compared to other two methods., Comment: Journal of Computing online at https://sites.google.com/site/journalofcomputing/

The Call admission control (CAC) is one of the Radio Resource Management (RRM) techniques that plays influential role in ensuring the desired Quality of Service (QoS) to the users and applications in next generation networks. This paper proposes a fuzzy neural approach for making the call admission control decision in multi class traffic based Next Generation Wireless Networks (NGWN). The proposed Fuzzy Neural call admission control (FNCAC) scheme is an integrated CAC module that combines the linguistic control capabilities of the fuzzy logic controller and the learning capabilities of the neural networks. The model is based on recurrent radial basis function networks which have better learning and adaptability that can be used to develop intelligent system to handle the incoming traffic in an heterogeneous network environment. The simulation results are optimistic and indicates that the proposed FNCAC algorithm performs better than the other two methods and the call blocking probability is minimal when compared to other two methods., Comment: International Journal of Computer Science Issues online at http://ijcsi.org/articles/A-QoS-Provisioning-Recurrent-Neural-Network-based-Call-Admission-Control-for-beyond-3G-Networks.php

We describe a unified approach for the determination of ac-Stark correction and Kramers-Heisenberg dispersion formula. In both cases the contribution from infinite intermediate summation appearing in the expression for the corresponding matrix elements are evaluated exactly in the dipole approximation for the ground state of hydrogen atom using a variation of the Dalgarno-Lewis method. The analytical expressions obtained can be efficiently used for the numerical evaluation of matrix element for all values of incident photon energy and comparison is made with results obtained by different methods., Comment: 6 pages, 3 tables