Optimal Measurement Strategy Research Articles

Practical Receiver for Optimal Discrimination of Binary Coherent Signals.

We address the long-standing problem of discriminating coherent states with the minimum error rate. We show an optimum receiver for coherent states which admits a relatively simple implementation with current technologies. The receiver is based on multichannel splitting of the signal, followed by feed-forward signal displacement and photon-counting detection. We develop an optimal control strategy for a finite signal split and show convergence of the error rate to the Helstrom bound.

Optimal measurements in phase estimation: simple examples

We identify optimal measurement strategies for phase estimation in different scenarios. For pure states of a single qubit, we show that optimal measurements form a broad set parametrized with a continuous variable. When the state is mixed this set reduces to merely two possible measurements. For two qubits, we focus on the symmetric Werner state. We find an optimal measurement and show that estimation from the population imbalance is optimal only if the state is pure. Finally, for a pure state of $N$ qubits, we finds under which conditions the estimation from the full $N$-body correlation and from the population imbalance are optimal.

Adaptive optimal measurement for the squeezed vacuum and coherent state

The output phase of the Sagnac interferometer has been measured with quantum balanced homodyne technique when coherent light and squeezed vacuum light are fed into the Sagnac interferometer simultaneously [Chen Kun et al., Acta Phys. Sin. 65 054203(2016)]. Nevertheless, there exist two deficiencies: 1) the phase sensitivity is related to the phase itself; 2) there are strict requirements for the phases of local oscillator light, coherent light and squeezed vacuum light. For overcoming these deficiencies, an adaptive optimal measurement scheme is suggested for the phase estimation. Firstly, we calculate that the quantum Fisher information (QFI) of the squeezed vacuum and coherent state is sinh2r+||2e2r by treating them as a quantum pure state, for they satisfy a condition of the quantum pure state, namely ()=()2. The QFI is related to quantum Cramer-Rao lower bound which can be used to evaluate the performance of the estimator. Secondly, we make an analysis of positive operator-valued measure (POVM) and design a set of the optimal measurement operators for reaching the quantum Cramer-Rao lower bound, whereas the optimal measurement operators depend on the true value of the phase which is what we want to estimate. In order to solve the problem and estimate the parameter effectively, an adaptive method is suggested. We set an initial value of the phase parameter to obtain a set of measurement operators which are not optimal at the first step. And then the initial measurement operators are used for POVM and to obtain a conditional probability function, from which we can obtain a new value of the phase with maximum likelihood estimator. Therefore, the measurement operators and conditional probability function will be updated with the new value. As the measurement operators and conditional probability function are updated step by step, we can estimate the value adaptively. In fact, the results of the maximum likelihood estimator will converge at the true value of the phase parameter gradually, which is then proved with the theoretical analysis. All in all, an adaptive measurement method of estimating the phase parameter of the squeezed vacuum and coherent state in Sagnac interferometer is suggested, and is proved theoretically to be that the scheme will converge at the true value of the phase with a probability of 1 and can reach the quantum Cramer-Rao lower bound.

Optimal Frames for Polarization State Reconstruction.

Complete determination of the polarization state of light requires at least four distinct projective measurements of the associated Stokes vector. Stability of state reconstruction, however, hinges on the condition number κ of the corresponding instrument matrix. Optimization of redundant measurement frames with an arbitrary number of analysis states, m, is considered in this Letter in the sense of minimization of κ. The minimum achievable κ is analytically found and shown to be independent of m, except for m=5 where this minimum is unachievable. Distribution of the optimal analysis states over the Poincaré sphere is found to be described by spherical 2 designs, including the Platonic solids as special cases. Higher order polarization properties also play a key role in nonlinear, stochastic, and quantum processes. Optimal measurement schemes for nonlinear measurands of degree t are hence also considered and found to correspond to spherical 2t designs, thereby constituting a generalization of the concept of mutually unbiased bases.

Syndrome measurement order for the [[7,1,3]] quantum error correction code

In this work, we explore the accuracy of quantum error correction depending of the order of the implemented syndrome measurements. CSS codes require that bit-flip and phase-flip syndromes be measured separately. To comply with fault-tolerant demands and to maximize accuracy, this set of syndrome measurements should be repeated allowing for flexibility in the order of their implementation. We examine different possible orders of Shor-state and Steane-state syndrome measurements for the [[7,1,3]] quantum error correction code. We find that the best choice of syndrome order, determined by the fidelity of the state after noisy error correction, will depend on the error environment. We also compare the fidelity when syndrome measurements are done with Shor states versus Steane states and find that Steane states generally, but not always, lead to final states with higher fidelity. Together, these results allow a quantum computer programmer to choose the optimal syndrome measurement scheme based on the system's error environment.

Defining success with HIV pre-exposure prophylaxis: a prevention-effective adherence paradigm.

Clinical trial data have shown that oral pre-exposure prophylaxis (PrEP) is efficacious when taken as prescribed; however, PrEP adherence is complex and must be understood within the context of variable risk for HIV infection and use of other HIV prevention methods. Different levels of adherence may be needed in different populations to achieve HIV prevention, and the optimal methods for achieving the necessary adherence for both individual and public health benefits are unknown. Guidance for PrEP use must consider these questions to determine the success of PrEP-based HIV prevention programs. In this article, we propose a new paradigm for understanding and measuring PrEP adherence, termed prevention-effective adherence, which incorporates dynamic HIV acquisition risk behaviors and the use of HIV alternative prevention strategies. We discuss the need for daily PrEP use only during periods of risk for HIV exposure, describe key issues for measuring and understanding relevant behaviors, review lessons from another health prevention field (i.e., family planning), and provide guidance for prevention-effective PrEP use. Moreover, we challenge emerging calls for sustained, near perfect PrEP adherence regardless of risk exposure and offer a more practical and public health-focused vision for this prevention intervention.

Syndrome measurement strategies for the [[7,1,3]] code

Quantum error correction (QEC) entails the encoding of quantum information into a QEC code space, measuring error syndromes to properly locate and identify errors, and, if necessary, applying a proper recovery operation. Here we compare three syndrome measurement protocols for the [[7,1,3]] QEC code: Shor states, Steane states, and one ancilla qubit by simulating the implementation of 50 logical gates with the syndrome measurements interspersed between the gates at different intervals. We then compare the fidelities for the different syndrome measurement types. Our simulations show that the optimal syndrome measurement strategy is generally not to apply syndrome measurements after every gate but depends on the details of the error environment. Our simulations also allow a quantum computer programmer to weigh computational accuracy versus resource consumption (time and number of qubits) for a particular error environment. In addition, we show that applying syndrome measurements that are unnecessary from the standpoint of quantum fault tolerance may be helpful in achieving better accuracy or in lowering resource consumption. Finally, our simulations demonstrate that the single-qubit non-fault-tolerant syndrome measurement strategy achieves comparable fidelity to those that are fault tolerant.

Method of Optimal Measurement Strategy for Ultra-High-Precision Machine in Roundness Nanometrology

Abstract Talyrond-TR is a modern sensitive instrument in nanometrology. The performance of Talyrond-TR machine is very important to find an optimal result in roundness measurement. In this paper, the experimental evaluation method of Talyrond-TR 73 machine is designed by using reference standard hemisphere. The influence of Talyrond machine performance in roundness measurement is presented. Signal responses of ten metrological strategic parameters have been analyzed and discussed. Deviation in roundness measurement strategies corresponding to four reference algorithms (LS), MZ, MC; MI) and two software fitting filters (2CR and Gaussian) with four spectral frequency ranges (1:15, 1:50, 1:150; 1:500 upr) are obtained through repeated arrangement, comparison and achieved. Experimental results revealed that the lowest deviation in roundness has been investigated by using MZ reference algorithm. The average of total roundness indicates low deviation by about 65.6% and 57.3% at using 2CR- and Gaussian-filter respectively, which proved the machine reliability within application range. Furthermore, the evaluation method was performed experimentally to establish reference data sets for circular, cylindrical and spherical objects. The sets of established data at different strategic parameters have been postulated to satisfy the ability of the proposed method to correlate the roundness measurements within the application range. The experimental result ensures that the proposed evaluation method is reliable and effective. Moreover, expanded uncertainty in measurement has been estimated and confirmed the degree of confidence for the proposed method.

Optimal measurement strategies for aboveground tree biomass in agricultural landscapes

Robust and cost effective methods for estimating aboveground biomass of trees on farms are necessary to understand the significance of this carbon pool, identify climate change mitigation opportunities and support smallholder farmers’ ability to capitalize on the emerging green economy. Using a dataset of 72 destructively sampled trees and 855 non-destructively sampled trees, we identified methodologically and economically efficient strategies to construct allometric equations and measure on-farm tree biomass. We found that robust biomass estimates can be obtained from measuring diameter at breast height (DBH) alone. Inclusion of tree height, specific wood density, and/or crown area in the allometric equation changed the biomass estimates by only 1.3 %, though these additional variables improved precision by reducing the error from 7.8 % to between 4.8 and 7.0 %. Research accuracy-to-cost trade-offs can be optimized by building equations based on destructive measurements of trees that span stem diameters found in the landscape; equations based on only small or large diameter trees result in poor estimates. Given (1) the resources required to measure additional dendrometric parameters in the field (2) the potential to introduce measurement errors that can propagate through estimates at farm and landscape scales, and (3) the need to quickly increase the amount of data available at low cost, we recommend that allometric equations for trees on farms be based solely on DBH and that the sampling strategy capture the range of tree sizes found in the landscape and future indirect quantification should focus on diameter at breast height as a predictor of biomass to save resources.

Research of DC Panel Battery Fault Detection Method

This paper elaborates the DC screen and battery DC screen fault detection method. The method of measuring battery’s internal resistance and voltage is analyzed and studied in this paper, and the two methods are optimized. Besides, the structure of the battery internal resistance, internal resistance equivalent principle and other aspects are also introduced in this paper. The optimal measurement scheme can be chosen by comparing the internal resistance measurement of DC discharge method and the AC signal injection method.

Quantum discord of ensemble of quantum states

We highlight an information-theoretic meaning of quantum discord as the gap between the ac- cessible information and the Holevo bound in the framework of ensemble of quantum states. This complementary relationship implies that a large amount of pre-existing arguments about the evaluation of quantum discord can be directly applied to the accessible information and vice versa. For an ensemble of two pure qubit states, we show that one can evade the optimization problem with the help of the Koashi-Winter relation. Further, for the general case (two mixed qubit states), we recover the main results presented by Fuchs and Caves [Phys. Rev. Lett. 73, 3047 (1994)], but totally from the perspective of quantum discord. Following this line of thought, we also investigate the geometric discord as an indicator of quantumness of ensembles in detail. Finally, we give an example to elucidate the difference between quantum discord and geometric discord with respect to optimal measurement strategies.

Modeling of the residual kinematic errors of coordinate measuring machines using LaserTracer system

The following article examines the methodology of identifying and modeling kinematic errors of coordinate measuring machines with the use of a modern and precise interferometric system—the LaserTracer. Since the kinematic errors of coordinate measuring machines (CMMs) are by far the most prevalent factor in measurement uncertainty, a specially developed model could be used for efficient uncertainty evaluation as an additional module of the virtual measuring machine responsible for simulation of the CMM kinematic errors. The model could also be of use for determining optimal measurement strategy, and would potentially improve the uncertainty of measurements performed.

Full counting statistics of generic spin entangler with quantum dot-ferromagnet detectors

Entanglement between spatially separated electrons in nanoscale transport is a fundamental property, yet to be demonstrated experimentally. Here we propose and analyse theoretically the transport statistics of a generic spin entangler coupled to a hybrid quantum dot-ferromagnet detector system. We show that the full distribution of charges arriving at the ferromagnetic terminals provides complete information on the spin state of the particles emitted by the entangler. This provides means for spin entanglement detection via electrical current correlations, with optimal measurement strategies depending on the a priori knowledge of ferromagnet polarization and spin-flip rates in the detector dots. The scheme is exemplified by applying it to Andreev and triple dot entanglers.

Optimization of quantum state tomography in the presence of experimental constraints

In the absence of experimental constraints, optimal measurement schemes for quantum state tomography are well understood. We consider the scenario where the experimenter doesn't have arbitrary freedom to construct their measurement set, and may therefore not be able to implement a known optimal scheme. We introduce a simple procedure for minimizing the uncertainty in the reconstructed quantum state for an arbitrary tomographic scheme. We do this by defining a figure of merit based on the equally weighted variance of the measurement statistics. This figure of merit is straightforwardly based on the singular value decomposition of the measurement matrix, making it well suited for optimization.

Aircraft mass budgeting to measure CO2 emissions of Rome, Italy

Aircraft measurements were used to estimate the CO2 emission rates of the city of Rome, assessed against high-resolution inventorial data. Three experimental flights were made, composed of vertical soundings to measure Planetary Boundary Layer (PBL) properties, and circular horizontal transects at various altitudes around the city area. City level emissions and associated uncertainties were computed by means of mass budgeting techniques, obtaining a positive net CO2 flux of 14.7 ± 4.5, 2.5 ± 1.2, and 10.3 ± 1.2 μmol m(-2) s(-1) for the three flights. Inventorial CO2 fluxes at the time of flights were computed by means of spatial and temporal disaggregation of the gross emission inventory, at 10.9 ± 2.5, 9.6 ± 1.3, and 17.4 ± 9.6 μmol m(-2) s(-1). The largest differences between the two dataset are associated with a greater variability of wind speed and direction in the boundary layer during measurements. Uncertainty partitioned into components related to horizontal boundary flows and top surface flow, revealed that the latter dominates total uncertainty in the presence of a wide variability of CO2 concentration in the free troposphere (up to 7 ppm), while it is a minor term with uniform tropospheric concentrations in the study area (within 2 ppm). Overall, we demonstrate how small aircraft may provide city level emission measurements that may integrate and validate emission inventories. Optimal atmospheric conditions and measurement strategies for the deployment of aircraft experimental flights are finally discussed.

Beam test of a one-dimensional position sensitive chamber on synchrotron radiation

A one-dimensional single-wire chamber was developed to provide high position resolution for powder diffraction experiments with synchrotron radiation. A diffraction test using the sample of SiO2 has been accomplished at 1W2B laboratory of Beijing Synchrotron Radiation Source. The data of the beam test were analyzed and some diffraction angles were obtained. The experimental results were in good agreement with standard data from ICDD powder diffraction file. The precision of diffraction angles was 1% to 4.7%. Most of the relative errors between measured values of diffraction angles and existing data were less than 1%. As for the detector, the best position resolution in the test was 138 μm (σ value) with an X-ray tube. Finally, discussions of the results were given. The major factor that affected the precision of measurement was deviation from the flat structure of the detector. The effect was analyzed and the conclusion was reached that it would be the optimal measurement scheme when the distance between the powder sample and detector was from 400 mm to 600 mm.

High-throughput powder X-ray diffraction, IR-spectroscopy and ion chromatography analysis of urinary stones: A comparative study

Abstract The instrumental qualitative analysis of urinary stones is a critical step in clinical practice and urological research. A powder X-ray diffraction, IR-spectroscopy and ion chromatography have been applied for the qualitative analysis of 20 urinary stones. Suggestions for a sample preparation and an optimal measurement strategy were formulated. The main difficulties for the powder X-ray diffraction qualitative analysis are a limiting amount of the sample and a preferential orientation of crystals, both issues should be minimized by the special sample preparation. Urinary stones samples have been clustered into four groups using different sets of numerical input data (cation and anion content, phase composition). At the same time a high-throughput multivariate clustering has been applied for powder X-ray diffraction and IR-spectroscopy data. The multivariate whole-profile approach can be used as a tool for a high-throughput time reducing technique for clinical practice, when a quick and stable classification of samples is required. All three sets of the data can be automatically separated into three clusters: oxalate-reach, oxalate-pure and non-oxalate samples. Uricite-pure and uricite-rich samples can be easily clustered.

Simultaneous optimization of harvest schedule and measurement strategy

In many recent studies, the value of forest inventory information in the harvest scheduling has been examined. Usually only the profitability of measuring simultaneously all the stands in the area is examined. Yet, it may be more profitable to concentrate the measurement efforts to some subset of them. In this paper, the authors demonstrate that stochastic optimization can be used for defining the optimal measurement strategy simultaneously with the harvest decisions. The results show that without end-inventory constraints, it was most profitable to measure the stands that were just below the medium age. Measuring the oldest stands was not profitable at all. It turned out to be profitable to postpone the measurements until just before the potential harvests. Introducing a strict end-inventory constraint increased the number of stands that could be profitably measured. In this case, also the length of the planning horizon had a clear effect on what stands were profitable to measure. With a 15-year planning horizon, measuring the oldest stands was profitable while with longer planning horizons it was not. The interest rate did not affect the number of stands measured much, but it had a clear effect on the timing of the measurements.

MEASUREMENT AND REPORTING OF RADON EXPOSURES.

Lung cancer risk caused by the inhalation of radon (222Rn) and its short-lived progeny is related to lung dose, which cannot be directly measured. The only measurable parameters which allow the determination of lung doses are the radon and radon progeny activity concentrations and related size distributions. Although lung cancers are caused by the inhaled short-lived radon progeny and not by the radon gas, it is the radon gas which is commonly measured and not its progeny. Since radon gas measurements are much easier to carry out, require less expensive equipment and are especially suited for long-term measurements, the report focuses on the measurement of the radon gas for specific exposure conditions in homes and workplaces. The first objective of this report is to provide information on how to measure radon, covering measurement techniques of radon in air and water, currently available detection systems, and measurement strategies most appropriate for the desired goal of a measurement campaign. Critical measurement strategy decisions are the selection of the measured radionuclide (i.e., radon gas or radon progeny and related size distributions), choice of the measurement period (i.e., short-term or long-term measurements), the choice of detector and its deployment, the type of measurement (i.e., areal or personal measurements), the survey strategy (i.e., integral or time-resolved measurements), or the strategy to accomplish the specific goal of a survey (i.e., measurements describing the current status or retrospective measurements). The choice of a specific strategy depends on the purpose of the survey, and differs therefore between the demands of a nation-wide indoor radon survey or an epidemiological study.The second objective of this report is how to interpret and report the results of these measurements, the associated uncertainties, and the resulting dosimetric estimates. Care should be taken when reporting and interpreting radon measurements because measured radon activity concentrations exhibit significant spatial variations (i.e., local and areal), and temporal variations (i.e., diurnal, seasonal, and annual). Consequently,estimates of the average annual radon activity concentrations are typically used for radon surveys and are compared with reference levels for radiation protection purposes. Other factors that may affect the interpretation of radon measurement results and the related dose estimates include thoron (220Rn) interference on radon detection systems, variations of aerosol parameters, equilibrium factor, duration of exposure (i.e., occupancy times in a building or location) and breathing rates. Often encountered problems are the uncertainties in extrapolating short-term measurements carried out at different locations within a building, or at different times during a year or in different years to statistically reasonable average values.Finally, the third objective of this report is to provide recommendations on optimal measurement strategies,measurement techniques, recording and reporting of measurements for different measurement objectives,such as individual exposure, average population exposure in a region or country, epidemiological studies or compliance with reference levels in radiation protection.

Quantum state discrimination bounds for finite sample size

In the problem of quantum state discrimination, one has to determine by measurements the state of a quantum system, based on the a priori side information that the true state is one of the two given and completely known states, ρ or σ. In general, it is not possible to decide the identity of the true state with certainty, and the optimal measurement strategy depends on whether the two possible errors (mistaking ρ for σ, or the other way around) are treated as of equal importance or not. Results on the quantum Chernoff and Hoeffding bounds and the quantum Stein's lemma show that, if several copies of the system are available then the optimal error probabilities decay exponentially in the number of copies, and the decay rate is given by a certain statistical distance between ρ and σ (the Chernoff distance, the Hoeffding distances, and the relative entropy, respectively). While these results provide a complete solution to the asymptotic problem, they are not completely satisfying from a practical point of view. Indeed, in realistic scenarios one has access only to finitely many copies of a system, and therefore it is desirable to have bounds on the error probabilities for finite sample size. In this paper we provide finite-size bounds on the so-called Stein errors, the Chernoff errors, the Hoeffding errors, and the mixed error probabilities related to the Chernoff and the Hoeffding errors.