Robust creation of atomic W state in a cavity by adiabatic passage

We propose two robust schemes to generate controllable (deterministic) atomic W-states of three three-level atoms interacting with an optical cavity and a laser beam. Losses due to atomic spontaneous emissions and to cavity decay are efficiently suppressed by employing adiabatic passage technique and appropriately designed atom-field couplings. In these schemes the three atoms traverse the cavity-mode and the laser beam and become entangled in the free space outside the cavity.Comment: 7 pages, 6 figures. Submitted to Optics Communication

Effect of spontaneous emission and cavity decay on intracavity stimulated Raman adiabatic passage

In this paper, we study the robust technique of stimulated Raman adiabatic passage in an optical cavity considering decoherence effects of atomic spontaneous emission and cavity decay. Numerical solution of Liouville equation shows that the population transfer of the system is more sensitive to the cavity decay than the atomic spontaneous emission

Quantum state engineering in ion-traps via adiabatic passage

We propose two relatively robust schemes to generate entangled W states of three (or generally N) ions in ion trap systems by using adiabatic passage technique and appropriately designed ion-field couplings in a single step. In the first scheme, we apply the N-pod fractional stimulated Raman adiabatic passage (F-STIRAP) technique to generate W state of N ions using two Gaussian laser pulses. We also show that the W state of N − 1 ions can be created via a simple N-pod standard STIRAP by two laser pulses. In the second scheme, we generate the entangled state of N ions via π-pulse technique by a single laser pulse. We also study the population transfer of the system by numerical solutions of the master equation, considering the effect of decoherence channels due to laser intensity fluctuations and dissipation in the phonon modes

Linear Regression under Partial Information

Often, we need to know how to estimate the value of a difficult-to-directly estimate quantity y -- e.g., tomorrow\u27s temperature -- based on the known values of several quantities x1, ..., xn. In many practical situations, we know that the relation between y and xi can be accurately described by a linear function. So, to find this dependence, we need to estimate the coefficients of this linear dependence based on the known cases in which we know both y and xi; this is known as linear regression. In the ideal situation, when in each case, we know all the inputs xi, the computationally efficient and well-justified least squares method provides a solution to this problem. However, in practice, some of the inputs are often missing. There are heuristic methods for dealing with such missing values, but the problem is that different methods lead to different results. This is the main problem with which we deal in this paper. To solve this problem, we propose a new well-justified method that eliminates this undesirable non-uniqueness. An auxiliary computational problem emerges if after we get a linear dependence of y on xi, we learn the values of an additional variable xn+1. In this case, in principle, we can simply re-apply the least square method from scratch , but this idea, while feasible, is still somewhat time-consuming, so it is desirable to come up with a faster algorithm that would utilize the previous regression result. Such an algorithm is also provided in this paper

How to Make Machine Learning Financial Recommendations More Fair: Theoretical Explanation

Machine learning has been actively and successfully used to make financial decisions. In general, these systems work reasonably well. However, in some cases, these systems show unexpected bias towards minority groups -- the bias that is sometime much larger than the bias in the data on which they were trained. A recent paper analyzed whether a proper selection of hyperparameters can decrease this bias. It turned out that while the selection of hyperparameters indeed affect the system\u27s fairness, only a few of the hyperparameters lead to consistent improvement of fairness: the number of features used for training and the number of training iterations. In this paper, we provide a theoretical explanation for these empirical results

Implementation of one-qubit holonomic rotation gate by adiabatic passage

We propose a robust scheme, using tripod stimulated Raman adiabatic passage, to generate one-qubit rotation gate. In this scheme, a four-level atom interacts with three resonant laser pulses and time evolution of the corresponding coherent system is designed such that the rotation gate is implemented at the end of process. Rotation angle in this gate is holonomic and has a geometrical basis in the parameter space. We also explore the effect of spontaneous emission on the population transfer with numerical solution of Schrödinger and Liouville equations

Occurrence and distribution of microplastic particles and the concentration of Di 2-ethyl hexyl phthalate (DEHP) in microplastics and wastewater in the wastewater treatment plant

Wastewater treatment plant (WWTP) is one of the significant sources of Microplastics (MPs) release to the environment. Di 2-ethyl hexyl phthalate (DEHP) is used as an additive for more flexibility of plastics. In this study, we determined the number, size, shape, and color distribution of MPs as well as the concentration of DEHP in MPs and wastewater during the wastewater treatment process in WWTP. Samples were collected from 4 stations of different treatment stages of WWTP. The microplastic particles and the concentration of DEHP were detected via the fluorescence and polarized light microscopy and GC/MS instrument, respectively. The number of MPs decreased from 9.2 (station 1) to 0.84 MP/L (the final treated effluent) during the wastewater treatment process. Also, the size of MPs at the last station was smaller than the other stations. The mean concentrations of DEHP in MPs in stations 1, 2, 3 and 4 had the respective values of 83.3, 61.05, 30.62 and 17.49 μg/g, while the mean concentrations of DEHP in wastewater in stations 1, 2, 3 and 4 were 30.08, 25.07, 9.56, and 8.13 μg/L, respectively. This study shows that despite the removal of high amounts of MPs and DEHP in the final effluent of WWTP, due to the high volume of this effluent (2.828 × 108 L/d), significant amount of MPs (2.419 × 107 MP/day) and DEHP enter the aquatic environment daily, which may threaten the health of the fish and aquatic organisms and ultimately on the health of the local population

Synthesis and characterization of γ-Fe2O3 encapsulated NaY zeolites as solid adsorbent for degradation of ceftriaxone through heterogeneous catalytic advanced oxidation processes

Abstract: The degradation of ceftriaxone (CTX) by heterogeneous catalytic advanced oxidation processes has been explored using γ-Fe2O3 NaY zeolites synthesized (γ-Fe2O3@NaY) in the laboratory through hydrothermal and chemical co-precipitation methods. γ-Fe2O3@NaY zeolite was characterized by scanning electron microscopy, energy-dispersive X-ray spectroscopy and X-ray diffractometer analyses. The effects of the initial concentration of CTX and catalyst, pH and hydrogen peroxide (H2O2) dose with the presence UV light on the degradation efficiency of CTX have been studied by conducting experiments in a batch reactor at room temperature. Experimental results reveal that CTX can be efficiently removed after 90 min at pH 4.0, CTX 20 mg/L, catalyst 1.17 g/L, H2O2 30 mM and presence of UV light. A kinetic and isotherm model was developed for investigation of the adsorption mechanism, and results show that model and data are in good agreement. The reusability of γ-Fe2O3@NaY was high as it degrades CTX in the presence of UV light and H2O2 even after five consecutive cycles. Also, due to having magnetic properties, this composite is easily separated from the solution by magnetism. This work indicates that bench synthesized γ-Fe2O3 NaY zeolite is a heterogeneous recoverable catalyst that can efficiently remove CTX from wastewater. Graphic abstract: [Figure not available: see fulltext.

Adjunctive treatment with aripiprazole for risperidone-induced hyperprolactinemia

Fatemeh Ranjbar,1 Homayoun Sadeghi-Bazargani,2,3 Parisa Niari Khams,1 Asghar Arfaie,1 Azim Salari,4 Mostafa Farahbakhsh1 1Clinical Psychiatry Research Center, Tabriz University of Medical Sciences, Tabriz, East Azerbaijan, Iran; 2Road Traffic Injury Research Center, Department of Statistics & Epidemiology, Tabriz University of Medical Sciences, Tabriz, Iran; 3World Health Organization Collaborating Center on Community Safety Promotion, Karolinska Institute, Stockholm, Sweden; 4Emam Khomeini Hospital, Naghadeh, West Azerbaijan, Iran Background: Antipsychotics have been used for more than 50 years in the treatment of schizophrenia and many other psychiatric disorders. Prolactin levels usually increase in patients treated with risperidone. Aripiprazole, which has a unique effect as an antipsychotic, is a D2 receptor partial agonist. It is an atypical antipsychotic with limited extrapyramidal symptoms. Since it acts as an antagonist in hyperdopaminergic conditions and as an agonist in hypodopaminergic conditions, it does not have adverse effects on serum prolactin levels. The present study aimed to investigate the effect of aripiprazole on risperidone-induced hyperprolactinemia. Methods: This before-and-after clinical trial was performed in 30 patients. Baseline prolactin levels were measured in all patients who were candidates for treatment with risperidone. In subjects with elevated serum prolactin, aripiprazole was added to their treatment. Serum prolactin levels were measured during the first week, second week, and monthly thereafter for at least 3 months or until prolactin levels became normal. The data were analyzed using Stata version 11 software. Survival analysis and McNemar’s test were also performed. Results: The mean age of the participants was 30.8 years. Prolactin levels normalized in 23 (77%) participants during the study, and menstrual disturbances normalized in 25 (83.3%). Prolactin levels normalized in most patients between days 50 and 110. The median time to recovery based on normalization of prolactin was 84 days. Psychotic symptoms were present in 26 subjects at baseline, but in only two by the end of the study. Conclusion: The results of this study confirm the effects of aripiprazole in reducing risperidone-induced hyperprolactinemia and its sequelae. Aripiprazole also led to significant improvements in psychotic symptoms when compared with those present prior to treatment with aripiprazole. Keywords: hyperprolactinemia, aripiprazole, risperidone, psychotic disorde