Quantum disentanglers

It is not possible to disentangle a qubit in an unknown state $|\psi>$ from a set of (N-1) ancilla qubits prepared in a specific reference state $|0>$. That is, it is not possible to {\em perfectly} perform the transformation $(|\psi,0...,0\r +|0,\psi,...,0\r +...+ |0,0,...\psi\r) \to |0,...,0>\otimes |\psi>$. The question is then how well we can do? We consider a number of different methods of extracting an unknown state from an entangled state formed from that qubit and a set of ancilla qubits in an known state. Measuring the whole system is, as expected, the least effective method. We present various quantum ``devices'' which disentangle the unknown qubit from the set of ancilla qubits. In particular, we present the optimal universal disentangler which disentangles the unknown qubit with the fidelity which does not depend on the state of the qubit, and a probabilistic disentangler which performs the perfect disentangling transformation, but with a probability less than one.Comment: 8 pages, 1 eps figur

Optimal Universal Disentangling Machine for Two Qubit Quantum States

We derive the optimal curve satisfied by the reduction factors, in the case of universal disentangling machine which uses only local operations. Impossibility of constructing a better disentangling machine, by using non-local operations, is discussed.Comment: 15 pages, 2 eps figures, 1 section added, 1 eps figure added, minor corrections, 2 reference numbers correcte

The intricate Galaxy disk: velocity asymmetries in Gaia-TGAS

We use the Gaia-TGAS data to compare the transverse velocities in Galactic longitude (coming from proper motions and parallaxes) in the Milky Way disk for negative and positive longitudes as a function of distance. The transverse velocities are strongly asymmetric and deviate significantly from the expectations for an axisymmetric Galaxy. The value and sign of the asymmetry changes at spatial scales of several tens of degrees in Galactic longitude and about 0.5 kpc in distance. The asymmetry is statistically significant at 95% confidence level for 57% of the region probed, which extends up to ~1.2 kpc. A percentage of 24% of the region studied shows absolute differences at this confidence level larger than 5 km/s and 7% larger than 10 km/s. The asymmetry pattern shows mild variations in the vertical direction and with stellar type. A first qualitative comparison with spiral arm models indicates that the arms are unlikely to be the main source of the asymmetry. We briefly discuss alternative origins. This is the first time that global all-sky asymmetries are detected in the Milky Way kinematics, beyond the local neighbourhood, and with a purely astrometric sample.Comment: Accepted for publication in A&A Letter

Quantitative Forecasting of Risk for PTSD Using Ecological Factors: A Deep Learning Application

Forecasting the risk for mental disorders from early ecological information holds benefits for the individual and society. Computational models used in psychological research, however, are barriers to making such predictions at the individual level. Preexposure identification of future soldiers at risk for posttraumatic stress disorder (PTSD) and other individuals, such as humanitarian aid workers and journalists intending to be potentially exposed to traumatic events, is important for guiding decisions about exposure. The purpose of the present study was to evaluate a machine learning approach to identify individuals at risk for PTSD using readily collected ecological risk factors, which makes scanning a large population possible. An exhaustive literature review was conducted to identify multiple ecological risk factors for PTSD. A questionnaire assessing these factors was designed and distributed among residents of southern Israel who have been exposed to terror attacks; data were collected from 1,290 residents. A neural network classification algorithm was used to predict the likelihood of a PTSD diagnosis. Assessed by cross-validation, the prediction of PTSD diagnostic status yielded a mean area under receiver operating characteristics curve of .91 (F score = .83). This study is a novel attempt to implement a neural network classification algorithm using ecological risk factors to predict potential risk for PTSD. Preexposure identification of future soldiers and other individuals at risk for PTSD from a large population of candidates is feasible using machine learning methods and readily collected ecological factors

Contraceptive trends and fetal outcome in women with short and long interpregnancy interval: a prospective observational study

Background: The present study was conducted at our tertiary health centre with the objective of analyzing contraceptive trends and fetal outcome in women with various interpregnancy interval (IPI). Methods: The present study was a prospective observational study. Women were segregated into three categories as per their IPI (short, normal and long) and contraceptive trends and fetal outcome were deliberated. All women attending ANC clinic with previous pregnancy, regardless of outcome and registration status were included in our study. Results: We found that 21.1% of women with short IPI were unaware about contraception and this difference was statistically significant. It was seen that among women not using any method of contraception, majority had short ICP, almost 31.1% cases. This difference was also statistically significant. Amidst those with adverse outcomes of previous pregnancy, i.e. 169 cases, 87 cases i.e. 51.5% of the women conceived within 2 years. Short IPI is linked with an escalated risk of low birth weight, preterm birth and congenital anomaly whereas long IPI caused large for gestational age babies. Conclusions: Contraception and previous pregnancy outcome have a significant effect on interpregnancy interval which in turn affects the maternal and fetal outcome. So it is essential to maintain an optimum interpregnancy interval as most of these complications are avoidable. Short interpregnancy interval is associated with low birth weight, preterm and congenital anomaly whereas long interpregnancy interval is associated with large for gestational age babies

Realization of Optimal Disentanglement by Teleportation via Separable Channel

We discuss here the best disentanglement processes of states of two two-level systems which belong to (i) the universal set, (ii) the set in which the states of one party lie on a single great circle of the Bloch sphere, and (iii) the set in which the states of one party commute with each other, by teleporting the states of one party (on which the disentangling machine is acting) through three particular type of separable channels, each of which is a mixture of Bell states. In the general scenario, by teleporting one party's state of an arbitrary entangled state of two two-level parties through some mixture of Bell states, we have shown that this entangled state can be made separable by using a physically realizable map $\tilde{V}$, acting on one party's states, if $\tilde{V} (I) = I, \tilde{V} ({\sigma}_j) = {\lambda}_j {\sigma}_j$, where ${\lambda}_j \ge 0$ (for $j = 1, 2, 3$), and ${\lambda}_1 + {\lambda}_2 + {\lambda}_3 \le 1$.Comment: 20 pages Late

Nonlinear Qubit Transformations

We generalise our previous results of universal linear manipulations [Phys. Rev. A63, 032304 (2001)] to investigate three types of nonlinear qubit transformations using measurement and quantum based schemes. Firstly, nonlinear rotations are studied. We rotate different parts of a Bloch sphere in opposite directions about the z-axis. The second transformation is a map which sends a qubit to its orthogonal state (which we define as ORTHOG). We consider the case when the ORTHOG is applied to only a partial area of a Bloch sphere. We also study nonlinear general transformation, i.e. (theta,phi)->(theta-alpha,phi), again, applied only to part of the Bloch sphere. In order to achieve these three operations, we consider different measurement preparations and derive the optimal average (instead of universal) quantum unitary transformations. We also introduce a simple method for a qubit measurement and its application to other cases.Comment: minor corrections. To appear in PR

An internet-based treatment for flying phobia using 360° images: A feasibility pilot study

Background: More research is needed in the field of Internet-delivered Cognitive Behavioral Treatments (ICBTs) for specific phobia in order to understand which characteristics are important in online exposure scenarios. The aim of the present work was to conduct a feasibility pilot study to explore participants'' opinions, preferences, and acceptability ratings of two types of images (still images vs 360° navigable images) in an ICBT for Flying Phobia (FP). A secondary aim was to test the potential effectiveness of the two active treatment arms compared to a waiting list control group. An exploratory aim was to compare the role of navigable images vs. still images in the level of sense of presence and reality judgment and explore their possible mediation in treatment effectiveness. Methods: Participants were randomly allocated to three conditions: NO-FEAR Airlines with still images (n = 26), NO-FEAR Airlines with still and navigable images (n = 26), and a waiting list group (n = 26). Primary outcome measures were participants'' opinions, preferences, satisfaction, and acceptance regarding the images used in the exposure scenarios. Secondary outcome measures included FP symptomatology outcomes and measures of sense of presence and reality judgment. Results: Participants in the study preferred navigable images over still images before and after treatment (over 84%), and they considered them more effective and logical for the treatment of their problem. However, adherence in the experimental conditions was low (42.3% dropout rate), and more participants withdrew from the group that included navigable images compared to the group that only included still images (14 vs. 8), with no statistical differences in attrition between the two conditions. NO-FEAR Airlines proved to be effective in reducing FP symptomatology compared to the control group, with large between-group effect sizes on all FP measures (ranging from 0.76 to 2.79). No significant mediation effect was found for sense of presence or reality judgment in treatment effectiveness. Discussion: The results of the current study suggest that participants prefer more immersive images in exposure scenarios, providing data that can help to design useful exposure scenarios to treat specific phobias in the future. They also provide evidence supporting the effectiveness of an ICBT for FP. Trial registration: Registered at Clinicaltrials.gov (NCT03900559) on April 9, 2019. Retrospectively registered. © 202

Design and SAR Analysis of Covalent Inhibitors Driven by Hybrid QM/MM Simulations

Quantum mechanics/molecular mechanics (QM/MM) hybrid technique is emerging as a reliable computational method to investigate and characterize chemical reactions occurring in enzymes. From a drug discovery perspective, a thorough understanding of enzyme catalysis appears pivotal to assist the design of inhibitors able to covalently bind one of the residues belonging to the enzyme catalytic machinery. Thanks to the current advances in computer power, and the availability of more efficient algorithms for QM-based simulations, the use of QM/MM methodology is becoming a viable option in the field of covalent inhibitor design. In the present review, we summarized our experience in the field of QM/MM simulations applied to drug design problems which involved the optimization of agents working on two well-known drug targets, namely fatty acid amide hydrolase (FAAH) and epidermal growth factor receptor (EGFR). In this context, QM/MM simulations gave valuable information in terms of geometry (i.e., of transition states and metastable intermediates) and reaction energetics that allowed to correctly predict inhibitor binding orientation and substituent effect on enzyme inhibition. What is more, enzyme reaction modelling with QM/MM provided insights that were translated into the synthesis of new covalent inhibitor featured by a unique combination of intrinsic reactivity, on-target activity, and selectivity