Sudden change in quantum and classical correlations and the Unruh effect

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Sudden change of quantum discord for a system of two qubits

It is known that quantum discord might experience a sudden transition in its dynamics when calculated for certain Bell-diagonal states (BDS) that are in interaction with their surroundings. We examine this phenomenon, known as the sudden change of quantum discord, considering the case of two qubits independently interacting with dephasing reservoirs. We first demonstrate that, for a class of initial states which can be chosen arbitrarily close to BDS, the transition is in fact not sudden, although it might numerically appear so if not studied carefully. Then, we provide an extension of this discussion covering the X-shaped density matrices. Our findings suggest that the transition of quantum discord might be sudden only for an highly idealized zero-measure subset of states within the set of all possible initial conditions of two qubits. © 2013 American Physical Society.

Non-Gaussianities from a sudden change in the inflaton speed of sound

Il concetto di inflazione e' stato introdotto nei primi anni ’80 per risolvere alcuni problemi del modello cosmologico standard, quali quello dell’orizzonte e quello della piattezza. Le predizioni dei piu' semplici modelli inflazionari sono in buon accordo con le osservazioni cosmologiche piu'recenti, che confermano sezioni spaziali piatte e uno spettro di fluttuazioni primordiali con statistica vicina a quella gaussiana. I piu' recenti dati di Planck, pur in ottimo accordo con una semplice legge di potenza per lo spettro a scale k > 0.08 Mpc−1 , sembrano indicare possibili devi- azioni a scale maggiori, seppur non a un livello statisticamente significativo a causa della varianza cosmica. Queste deviazioni nello spettro possono essere spiegate da modelli inflazionari che includono una violazione della condizione di lento rotolamento (slow-roll ) e che hanno precise predizioni per lo spettro. Per uno dei primi modelli, caratterizzato da una discontinuita' nella derivata prima del potenziale proposto da Starobinsky, lo spettro ed il bispettro delle fluttuazioni primordiali sono noti analiticamente. In questa tesi estenderemo tale modello a termini cinetici non standard, calcolandone analiticamente il bispettro e confrontando i risultati ottenuti con quanto presente in letteratura. In particolare, l’introduzione di un termine cinetico non standard permettera' di ottenere una velocita' del suono per l’inflatone non banale, che consentira' di estendere i risultati noti, riguardanti il bispettro, per questo modello. Innanzitutto studieremo le correzioni al bispettro noto in letteratura dovute al fatto che in questo caso la velocita' del suono e' una funzione dipendente dal tempo; successivamente, cercheremo di calcolare analiticamente un ulteriore contributo al bispettro proporzionale alla derivata prima della velocita' del suono (che per il modello originale e' nullo).

Experimental detection of sudden stiffness change in a structural system employing Laser Doppler Vibrometry

Sudden changes in the stiffness of a structure are often indicators of structural damage. Detection of such sudden stiffness change from the vibrations of structures is important for Structural Health Monitoring (SHM) and damage detection. Non-contact measurement of these vibrations is a quick and efficient way for successful detection of sudden stiffness change of a structure. In this paper, we demonstrate the capability of Laser Doppler Vibrometry to detect sudden stiffness change in a Single Degree Of Freedom (SDOF) oscillator within a laboratory environment. The dynamic response of the SDOF system was measured using a Polytec RSV-150 Remote Sensing Vibrometer. This instrument employs Laser Doppler Vibrometry for measuring dynamic response. Additionally, the vibration response of the SDOF system was measured through a MicroStrain G-Link Wireless Accelerometer mounted on the SDOF system. The stiffness of the SDOF system was experimentally determined through calibrated linear springs. The sudden change of stiffness was simulated by introducing the failure of a spring at a certain instant in time during a given period of forced vibration. The forced vibration on the SDOF system was in the form of a white noise input. The sudden change in stiffness was successfully detected through the measurements using Laser Doppler Vibrometry. This detection from optically obtained data was compared with a detection using data obtained from the wireless accelerometer. The potential of this technique is deemed important for a wide range of applications. The method is observed to be particularly suitable for rapid damage detection and health monitoring of structures under a model-free condition or where information related to the structure is not sufficient.

Paleoenvironmental change in the middle Okinawa Trough since the last deglaciation: Evidence from the sedimentation rate and planktonic foraminiferal record

Well-dated, high-resolution records of planktonic foraminifera and oxygen isotopes from two sediment cores, A7 and E017, in the middle Okinawa Trough reveal strong and rapid millennial-scale climate changes since similar to 18 to 17 thousand years before present (kyr B.P.). Sedimentation rate shows a sudden drop at similar to 11.2 cal. kyr B.P. due to a rapid rise of sea level after the Younger Dryas (YD) and consequently submergence of the large continental shelf on the East China Sea (ECS) and the retreat of the estuary providing sediment to the basin. During the last deglaciation, the relative abundance of warm and cold species of planktonic foraminifera fluctuates strongly, consistent with the timing of sea surface temperature (SST) variations determined from Mg/Ca measurements of planktonic foraminifera from one of the two cores. These fluctuations are coeval with climate variation recorded in the Greenland ice cores and North Atlantic sediments, namely Heinrich event 1 (H1), Bolling-Allerod (B/A) and YD events. At about 9.4 kyr B.P., a sudden change in the relative abundance of shallow to deep planktonic species probably indicates a sudden strengthening of the Kuroshio Current in the Okinawa Trough, which was synchronous with a rapid sea-level rise at 9.5-9.2 kyr B.P. in the ECS, Yellow Sea (YS) and South China Sea (SCS). The abundance of planktonic foraminiferal species, together with Mg/Ca based SST, exhibits millennial-scale oscillations during the Holocene, with 7 cold events (at about 1.7, 2.3-4.6, 6.2, 7.3, 8.2, 9.6, 10.6 cal. kyr BP) superimposed on a Holocene warming trend. This Holocene trend, together with centennial-scale SST variations superimposed on the last deglacial trend, suggests that both high and low latitude influences affected the climatology of the Okinawa Trough. (c) 2006 Elsevier B.V. All rights reserved.

Permutation Entropy Based Analysis of Complex Signals for Characterising Change in System Dynamics

Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.

Analysis of distrubances in large interconnected power systems

World economies increasingly demand reliable and economical power supply and distribution. To achieve this aim the majority of power systems are becoming interconnected, with several power utilities supplying the one large network. One problem that occurs in a large interconnected power system is the regular occurrence of system disturbances which can result in the creation of intra-area oscillating modes. These modes can be regarded as the transient responses of the power system to excitation, which are generally characterised as decaying sinusoids. For a power system operating ideally these transient responses would ideally would have a “ring-down” time of 10-15 seconds. Sometimes equipment failures disturb the ideal operation of power systems and oscillating modes with ring-down times greater than 15 seconds arise. The larger settling times associated with such “poorly damped” modes cause substantial power flows between generation nodes, resulting in significant physical stresses on the power distribution system. If these modes are not just poorly damped but “negatively damped”, catastrophic failures of the system can occur. To ensure system stability and security of large power systems, the potentially dangerous oscillating modes generated from disturbances (such as equipment failure) must be quickly identified. The power utility must then apply appropriate damping control strategies. In power system monitoring there exist two facets of critical interest. The first is the estimation of modal parameters for a power system in normal, stable, operation. The second is the rapid detection of any substantial changes to this normal, stable operation (because of equipment breakdown for example). Most work to date has concentrated on the first of these two facets, i.e. on modal parameter estimation. Numerous modal parameter estimation techniques have been proposed and implemented, but all have limitations [1-13]. One of the key limitations of all existing parameter estimation methods is the fact that they require very long data records to provide accurate parameter estimates. This is a particularly significant problem after a sudden detrimental change in damping. One simply cannot afford to wait long enough to collect the large amounts of data required for existing parameter estimators. Motivated by this gap in the current body of knowledge and practice, the research reported in this thesis focuses heavily on rapid detection of changes (i.e. on the second facet mentioned above). This thesis reports on a number of new algorithms which can rapidly flag whether or not there has been a detrimental change to a stable operating system. It will be seen that the new algorithms enable sudden modal changes to be detected within quite short time frames (typically about 1 minute), using data from power systems in normal operation. The new methods reported in this thesis are summarised below. The Energy Based Detector (EBD): The rationale for this method is that the modal disturbance energy is greater for lightly damped modes than it is for heavily damped modes (because the latter decay more rapidly). Sudden changes in modal energy, then, imply sudden changes in modal damping. Because the method relies on data from power systems in normal operation, the modal disturbances are random. Accordingly, the disturbance energy is modelled as a random process (with the parameters of the model being determined from the power system under consideration). A threshold is then set based on the statistical model. The energy method is very simple to implement and is computationally efficient. It is, however, only able to determine whether or not a sudden modal deterioration has occurred; it cannot identify which mode has deteriorated. For this reason the method is particularly well suited to smaller interconnected power systems that involve only a single mode. Optimal Individual Mode Detector (OIMD): As discussed in the previous paragraph, the energy detector can only determine whether or not a change has occurred; it cannot flag which mode is responsible for the deterioration. The OIMD seeks to address this shortcoming. It uses optimal detection theory to test for sudden changes in individual modes. In practice, one can have an OIMD operating for all modes within a system, so that changes in any of the modes can be detected. Like the energy detector, the OIMD is based on a statistical model and a subsequently derived threshold test. The Kalman Innovation Detector (KID): This detector is an alternative to the OIMD. Unlike the OIMD, however, it does not explicitly monitor individual modes. Rather it relies on a key property of a Kalman filter, namely that the Kalman innovation (the difference between the estimated and observed outputs) is white as long as the Kalman filter model is valid. A Kalman filter model is set to represent a particular power system. If some event in the power system (such as equipment failure) causes a sudden change to the power system, the Kalman model will no longer be valid and the innovation will no longer be white. Furthermore, if there is a detrimental system change, the innovation spectrum will display strong peaks in the spectrum at frequency locations associated with changes. Hence the innovation spectrum can be monitored to both set-off an “alarm” when a change occurs and to identify which modal frequency has given rise to the change. The threshold for alarming is based on the simple Chi-Squared PDF for a normalised white noise spectrum [14, 15]. While the method can identify the mode which has deteriorated, it does not necessarily indicate whether there has been a frequency or damping change. The PPM discussed next can monitor frequency changes and so can provide some discrimination in this regard. The Polynomial Phase Method (PPM): In [16] the cubic phase (CP) function was introduced as a tool for revealing frequency related spectral changes. This thesis extends the cubic phase function to a generalised class of polynomial phase functions which can reveal frequency related spectral changes in power systems. A statistical analysis of the technique is performed. When applied to power system analysis, the PPM can provide knowledge of sudden shifts in frequency through both the new frequency estimate and the polynomial phase coefficient information. This knowledge can be then cross-referenced with other detection methods to provide improved detection benchmarks.

Designing a new robust on-line secondary path modeling technique for feedforward active noise control systems

Several approaches have been introduced in the literature for active noise control (ANC) systems. Since the filtered-x least-mean-square (FxLMS) algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of the FxLMS algorithm, as a first novelty. In many ANC applications, an on-line secondary path modeling method using white noise as a training signal is required to ensure convergence of the system. As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feed forward ANC systems. The proposed algorithm is designed so that the noise injection is stopped at the optimum point when the modeling accuracy is sufficient. In this approach, a sudden change in the secondary path during operation makes the algorithm reactivate injection of the white noise to re-adjust the secondary path estimate. Comparative simulation results shown in this paper indicate the effectiveness of the proposed approach in reducing both narrow-band and broad-band noise. In addition, the proposed ANC system is robust against sudden changes of the secondary path model.

An efficient online secondary path estimation for feedback active noise control systems

In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.

Benefiting white noise in developing feedforward active noise control systems

In many applications of active noise control (ANC), an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to adjust the secondary path estimation. Comparative simulation results shown in this paper indicate effectiveness of the proposed method.

Portrait of the artist as a feminist, practice-led researcher

Becoming a researcher, like any process of cultural initiation, is a complicated negotiation of processes and identity. While it is tempting to imagine that a researcher is just 'one who researches', the reality is far more complex and can be thought of as a journey rather than a sudden change of role. In practice-led research there is often a final and difficult assessment that needs to be made of that journey, and this requires the collation and integration of seemingly schizophrenic elements into one coherent body of findings. This paper attempts to outline the underlying “system of methods used in a particular area of study or activity” that have defined my research journey. It discusses the various elements that have informed and directed this enquiry, which include, but are not limited to: practice-led research, reflexivity, and post/academic writing, all underpinned by a feminist approach.

Unsteady Compressible Boundary-Layer Flow On The Stagnation Line Of An Infinite Swept Cylinder

Numerical solutions of flow and heat transfer process on the unsteady flow of a compressible viscous fluid with variable gas properties in the vicinity of the stagnation line of an infinite swept cylinder are presented. Results are given for the case where the unsteady temperature field is produced by (i) a sudden change in the wall temperature (enthalpy) as the impulsive motion is started and (ii) a sudden change in the free-stream velocity. Solutions for the simultaneous development of the thermal and momentum boundary layers are obtained by using quasilinearization technique with an implicit finite difference scheme. Attention is given to the transient phenomenon from the initial flow to the final steady-state distribution. Results are presented for the skin friction and heat transfer coefficients as well as for the velocity and enthalpy profiles. The effects of wail enthalpy parameter, sweep parameter, fluid properties and transpiration cooling on the heat transfer and skin friction are considered.

Rapidly solidified Al–Cr alloys: Crystalline and quasicrystalline phases

Rapidly solidified Al–Cr alloys up to 20 at. % Cr were studied to delineate the extent of crystalline and quasicrystalline phase formation in these alloys in comparison with as-cast alloys by using transmission electron microscopy and x-ray diffraction technique. The icosahedral quasicrystals are observed from 7 to 15 at. % Cr alloys, while equilibrium ?–Al11Cr2 phase is completely absent. Both rapid solidification and subsequent thermal decomposition studies indicate that the main competing phase is ?–Al2Cr up to 15 at. % Cr. Beyond this composition ?–Al4Cr is the dominant phase together with a small amount of ?4–Al7Cr3. We have shown that the electron diffraction patterns of Al–Cr quasicrystals are often associated with a diffuse intensity distribution, indicative of short-range order. The change in quasilattice constant with composition suggests the existence of structural vacancies. Further, a sudden change from coarse to ultrafine quasicrystalline grain structure in Al-7 at. % Cr alloy points to a change in nucleation mechanism from heterogeneous to homogeneous mode during the rapid solidification.