State Dependence Research Articles

Bases for optimising stabiliser decompositions of quantum states

Stabiliser states play a central role in the theory of quantum computation. For example, they are used to encode computational basis states in the most common quantum error correction schemes. Arbitrary quantum states admit many stabiliser decompositions: ways of being expressed as a superposition of stabiliser states. Understanding the structure of stabiliser decompositions has significant applications in verifying and simulating near-term quantum computers. We introduce and study the vector space of linear dependencies of n-qubit stabiliser states. These spaces have canonical bases containing vectors whose size grows exponentially in n. We construct elegant bases of linear dependencies of constant size three. Critically, our sparse bases can be computed without first compiling a dictionary of all n-qubit stabiliser states. We utilise them to explicitly compute the stabiliser extent of states of more qubits than is feasible with existing techniques. Finally, we delineate future applications to improving theoretical bounds on the stabiliser rank of magic states.

Temperature Dependence of the Defect States in LWIR (100) and (111)B HgCdTe Epilayers for IR HOT Detectors

HgCdTe epilayers grown by chemical vapor deposition (MOCVD) on GaAs substrates operating in the long-wave infrared range were characterized by the photoluminescence (PL) method. Photodiode and photoconductor designs, both (100) and (111)B crystallographic, were analyzed. Spectral current responsivity (RI) and a PL signal approximated by a theoretical expression being the product of the density of states and the Fermi–Dirac distribution were used to determine the fundamental transition (energy gap, Eg). For all the samples, an additional deep-level-related transition associated with mercury vacancies (VHg) were observed. The energy distance of about 80 meV above the valence band edge was observed for all the samples. Moreover, measurements at low temperature showed shallow acceptor-level (AsTe and VHg as acceptors) transitions. In HgCdTe(100), due to the higher arsenic activation, AsTe was the dominant acceptor dopant, while, in HgCdTe(111)B, the main acceptor level was formed by the neutral VHg. The determined activation energies for AsTe and VHg dopants were of about 5 meV and 10 meV, respectively.

Multi-View Multi-Label Fine-Grained Emotion Decoding From Human Brain Activity.

Decoding emotional states from human brain activity play an important role in the brain-computer interfaces. Existing emotion decoding methods still have two main limitations: one is only decoding a single emotion category from a brain activity pattern and the decoded emotion categories are coarse-grained, which is inconsistent with the complex emotional expression of humans; the other is ignoring the discrepancy of emotion expression between the left and right hemispheres of the human brain. In this article, we propose a novel multi-view multi-label hybrid model for fine-grained emotion decoding (up to 80 emotion categories) which can learn the expressive neural representations and predict multiple emotional states simultaneously. Specifically, the generative component of our hybrid model is parameterized by a multi-view variational autoencoder, in which we regard the brain activity of left and right hemispheres and their difference as three distinct views and use the product of expert mechanism in its inference network. The discriminative component of our hybrid model is implemented by a multi-label classification network with an asymmetric focal loss. For more accurate emotion decoding, we first adopt a label-aware module for emotion-specific neural representation learning and then model the dependency of emotional states by a masked self-attention mechanism. Extensive experiments on two visually evoked emotional datasets show the superiority of our method.

Local-manifold-distance-based regression: an estimation method for quantifying dynamic biological interactions with empirical time series.

Quantifying species interactions based on empirical observations is crucial for ecological studies. Advancements in nonlinear time-series analyses, particularly S-maps, are promising for high-dimensional and non-equilibrium ecosystems. S-maps sequentially perform a local linear model fitting to the time evolution of neighbouring points on the reconstructed attractor manifold, and the coefficients can approximate the Jacobian elements corresponding to interaction effects. However, despite that the advantages in nonlinear forecasting with noise-contaminated data, these methodologies have a limitation in the Jacobian estimation accuracy owing to non-equidistantly stretched local manifolds in the state space. Herein, we therefore introduced a local manifold distance (LMD) concept, a non-equidistant measure based on the multi-faceted state dependency. By integrating LMD with advanced computation techniques, we presented a robust and efficient analytical method, LMD-based regression (LMDr). To validate its advantages in prediction and Jacobian estimation, we analysed synthetic time series of model ecosystems with different noise levels and applied it to an experimental protozoan predator-prey system with established biological information. The robustness to noise was the highest for LMDr, which also showed a better correspondence to expected predator-prey interactions in the protozoan system. Thus, LMDr can be applied to study complex ecological networks under dynamic conditions.

Tracking time-varying brand equity using household panel data

This paper proposes a novel yet simple approach for tracking time-varying utility-based brand equity using household panel data. Our two-stage procedure allows us to estimate a discrete choice model that explicitly accounts for consumer heterogeneity, state dependence, price endogeneity, and dynamic brand equity. We present dynamic brand utility as a time-varying measure that adds to current market-based or mindset metrics. An empirical study of household purchases in the detergent category reveals that brand equity varies over time. The temporal changes in the brand equity of single brands and the differences across brands have significant implications for consumers’ brand choice and, consequently, for brand management. Therefore, the dynamic utility-based model offers valuable support for tracking a brand’s state, including the brand’s competition, and for making appropriate marketing decisions.

A cycle or a tunnel? A study on unemployment and low-pay dynamics in Italy

We study the extent of persistence in unemployment and low-pay employment in Italy in the period 2014-2017, using the Italian component of the EU-SILC survey merged with administrative data. We model persistence in unemployment and low-pay employment using different dynamic random-effects models accounting for observed and latent individual heterogeneity as well as endogeneity of the initial conditions. We find evidence of true state dependence in place for both unemployment and low-pay employment. Moreover, past unemployment spells increase the probability of being low-paid, conditional on being employed, while the opposite effect is limited. For both processes the degree of reliance on the previous state is considerably greater than the magnitude of cross-effects. Thus, evidence is presented that these processes shape almost independent no-pay/low-pay tunnels leading individuals into two different traps, rather than a cycle between the two states.

Manipulating Ion Transport Regimes in Nanomembranes via a "Pore-in-Pore" Approach Enabled by the Synergy of Metal-Organic Frameworks and Solid-State Nanochannels.

Solid-state nanochannels (SSNs) have emerged as promising platforms for controlling ionic transport at the nanoscale. SSNs are highly versatile, and this feature can be enhanced through their combination with porous materials such as Metal-Organic Frameworks (MOF). By selection of specific building blocks and experimental conditions, different MOF architectures can be obtained, and this can influence the ionic transport properties through the nanochannel. Herein, we study the effects of confined synthesis of Zr-based UiO-66 MOF on the ion transport properties of single bullet-shaped poly(ethylene terephthalate) (PET) nanochannels. We have found that emerging textural properties from the MOF phase play a determinant role in controlling ionic transport through the nanochannel. We demonstrate that a transition from ion current saturation regimes to diode-like regimes can be obtained by employing different synthetic approaches, namely, counterdiffusion synthesis, where MOF precursors are kept separate and forced to diffuse through the nanochannel, and one-pot synthesis, where both precursors are placed at both ends of the channel. Also, by considering the dependence of the charge state of the UiO-66 MOF on the protonation degree, pH changes offered a mechanism to tune the iontronic output (and selectivity) among different regimes, including anion-driven rectification, cation-driven rectification, ion current saturation, and ohmic behavior. Furthermore, Poisson-Nernst-Planck (PNP) simulations were employed to rationalize the different iontronic outputs observed experimentally for membranes modified by different methods. Our results demonstrate a straightforward tool to synthesize MOF-based SSN membranes with tunable ion transport regimes.

THE MODELLING OF A HYSTERESIS GRAPH OF PIEZOELECTRIC ELEMENTS USING DEEP LEARNING BIDIRECTIONAL LSTM

The phenomenon of hysteresis is an integral part of dynamic systems in many fields of science such as physics, chemistry, biology and many more. It describes an inherent dependence of a system state based on the history of varying number of its previous states. Hysteresis can manifest as a dynamic lag between an input signal and an output system behaviour, which depends on the degree of that system dy-namics. Modelling systems containing hysteresis is a challenging mathematical task given their highly non-linear behaviour. This paper discusses and develop a deep learning model using bidirectional LSTM (long short-term memory) for predicting voltages necessary to stimulate a piezoelectric element to produce displacements in order to cancel or minimize vibrations. The predicted voltages rely on given displacements and time domain of the initial noise input. This noise input can then be amplified to match the resonance frequency of another piezoelectric element to generate the maximum voltage capable by this later piezoelectric element. This sinusoidal voltage then travels to a piezoelectric actuator to generate displacement that can cancel the initial noise. The model resulted a coefficient of determination score of 0.99983, a loss score of 0.0092 and MSE (mean squared error) of 8.5568e-05. Created model has proven that machine learning is a viable method for hysteresis modelling and can be further improved with increased input data availability and further investigation into different deep learning algorithms.

Метод визначення вібраційних характеристик промислового обладнання в частотній та часовій областях

This paper proposes hardware and software solutions and a data processing method for vibration diagnostics of industrial equipment, which uses discrete Fourier transform and Allan dispersion to increase the accuracy and stability of measurement processes and result processing. The object of this study is the use of vibration diagnostic methods to implement the concept of maintenance of industrial equipment based on monitoring its current and future condition. The subject of this research is the hardware and software solutions for vibration diagnostics systems and methods for processing measurement results. The purpose of this work is to develop a new resource-saving IoT-oriented wireless solution for vibration diagnostics, where the contact method and MEMS accelerometers are used to measure vibration parameters and to evaluate the effectiveness of new methods and algorithms for processing experimental data. The task: justify the need to find new hardware and software solutions and methods of processing the obtained results for the implementation of the service concept based on the tracking of vibration indicators of technical equipment; provide basic hardware and software solutions for the implementation of the cloud platform of vibration diagnostics; develop methods of processing results; check the developed methods and algorithms using mathematical modeling methods and in an on-site experiment; compare the effectiveness of own and competitive solutions; draw conclusions and formulate a plan for further research. Conclusions. It has been proven that the combination of known analysis methods in the time and frequency domains with multi-level processing gives better results than analogous methods. The developed hardware and software tools and the method of processing measurement results effectively implement the contact method of vibration measurement, which provides the possibility of tracking the state of technical equipment. The developed equipment for the calibration of vibration acceleration sensors can reduce accelerometer errors. Further areas of research are the search for the optimal distribution of calculations on IoT levels, reducing the computational complexity of algorithms, increasing the time of continuous autonomous operation of the lower-level microcontroller, creating micro services for time-series analysis, and researching the dependence of the technical state of the equipment on the calculated Allan deviation.

STATE-DEPENDENCY IN THE NEXUS BETWEEN DIGITAL FINANCIAL INCLUSION AND ECONOMIC GROWTH IN SUB-SAHARAN AFRICA

Objective: The objective of this study is to investigate state-dependency in the nexus between digital financial inclusion and economic growth in sub-Saharan Africa, with the aim of examining the impact of adopting digital financial technology to reduce financial exclusion and contribute to economic growth. Theoretical Framework: The paper extends the work of Sarma (2008) and Khera et al. (2021), by creating a new financial inclusion index that captures both traditional and digital financial inclusion. Method: The methodology adopted for this research comprises the principal component analysis (PCA) to identify signals in financial inclusion indicators, thereafter financial inclusion indexes for digital and traditional financial services were constructed. The panel quantile regression methodology was employed to analyse the impact of shocks and determine state dependency in the nexus, respectively. Data collection was carried out through secondary sources. Results and Discussion: The result confirms a positive relationship between digital financial inclusion and economic growth with the greatest impact in countries with lower real GDP, confirming state dependency. Research Implications: The findings suggest that policymakers should focus on promoting digital financial inclusion, particularly in countries with low to intermediate levels of income. Originality/Value: This study contributes to the literature by broadening the definition of digital financial inclusion beyond what is currently found in the literature to include vital financial inclusion dimensions such as access to financial services. The relevance and value of this research are further evidenced by the consideration of state-dependency in the relationship between financial inclusion and growth.

Path-dependence of the Plio–Pleistocene glacial/interglacial cycles

We find strong path dependence in the evolution of the Plio-Pleistocene glaciations using CLIMBER-2 Earth System Model simulations from the mid-Pliocene to modern preindustrial (3 My-0 My BP) driven by a gradual decrease in volcanic carbon dioxide outgassing and regolith removal from basal ice interaction. Path dependence and hysteresis are investigated by alternatively driving the model forward and backward in time. Initiating the model with preindustrial conditions and driving the model backward using time-reversed forcings, the increase in volcanic outgassing back-in-time (BIT) does not generate the high CO2 levels and relatively ice-free conditions of the late Pliocene seen in forward-in-time (FIT) simulations of the same model. This behavior appears to originate from nonlinearities and initial state dependence in the carbon cycle. A transition from low-amplitude sinusoidal obliquity (~41 ky) and precession (~23 ky) driven glacial/interglacial cycles to high-amplitude ~100 ky likely eccentricity-related sawtooth cycles seen between -1.25 My and -0.75 My BP (the Mid-Pleistocene transition or "MPT") in FIT simulations disappears in BIT integrations depending on the details of how the regolith removal process is treated. A transition toward depleted regolith and lowered atmospheric CO2 levels are both required to reproduce the MPT.

Velocity and Temperature Dependence of Steady‐State Friction of Natural Gouge Controlled by Competing Healing Mechanisms

AbstractThe empirical rate‐ and state‐dependent friction law is widely used to explain the frictional resistance of rocks. However, the constitutive parameters vary with temperature and sliding velocity, preventing extrapolation of laboratory results to natural conditions. Here, we explain the frictional properties of natural gouge from the San Andreas Fault, Alpine Fault, and the Nankai Trough from room temperature to ∼300°C for a wide range of slip‐rates with constant constitutive parameters by invoking the competition between two healing mechanisms with different thermodynamic properties. A transition from velocity‐strengthening to velocity‐weakening at steady‐state can be attained either by decreasing the slip‐rate or by increasing temperature. Our study provides a framework to understand the physics underlying the slip‐rate and state dependence of friction and the dependence of frictional properties on ambient physical conditions.

Assessment of the stress-strain state of slopes in landslide-prone areas where critical infrastructure facilities are located

Purpose. Ensure the integrity of landslide-prone areas through a developed method for assessing the stress-strain state of slopes based on seismic wave registration. The methods. To solve these tasks, the following steps were conducted: calculation of shear stresses and relative deformations of the landslide-prone soil area; registration of seismic vibrations using a MiniMateplus seismograph, determining the amplitudes of mass vibration velocities and frequency characteristics by components (tangential, vertical, radial), and identification of critical points based on shear stress magnitudes and relative deformations that are close to or exceed critical values. Findings. Through the registration of frequency characteristics at specified distances along the entire profile, it is possible not only to assess the hazard level of soil slopes at each point but also to create conditions ensuring necessary stability against additional special loads. The originality. The study introduces a method for monitoring landslide-prone areas based on seismic data analysis. For the first time, the dependency of stress-strain states of slopes in landslide-prone areas on the impact of amplitude frequencies of multiple stepwise free-fall drops of a load (artificial shock) is established through the registration of artificially induced seismic waves. The method considers only those shear stresses and relative deformations whose magnitudes are close to or exceed critical values within the same frequency range. It has been determined that resonance phenomena occur at specific frequencies, which can initiate landslide processes. The slope stability assessment method has further evolved to account not only for the current state of soil slope hazards but also to ensure stability against additional dynamic loads. Practical implementation. Experimental studies have established that to ensure the seismic resistance of critical infrastructure objects, it is necessary to consider not only the mass vibration velocity of soil particles but also the frequency characteristics of the object itself.

State-independent black hole interiors from the crossed product

Opinion is divided about the nature of state dependence in the black hole interior. Some argue that it is a necessary feature, while others argue it is a bug. In this paper, we consider the extended half-sided modular translation U (s0) (with s0 > 0) of Leutheusser and Liu that takes us inside the horizon. We note that we can use this operator to construct a modular Hamiltonian H and a conjugation J on the infalling time-evolved wedges. The original thermofield double translates to a new cyclic and separating vector in the shifted algebra. We use these objects and the Connes’ cocycle to repeat Witten’s crossed product construction in this new setting, and to obtain a Type II∞ algebra that is independent of the various choices, in particular that of the cyclic separating vector. Our emergent times are implicitly boundary-dressed. But if one admits an “extra” observer in the interior, we argue that the (state-independent) algebra can be Type I or Type II1 instead of Type II∞, depending on whether the observer’s light cone contains an entire Cauchy slice or not. Along with these general considerations, we present some specific calculations in the setting of the Poincare BTZ black hole. We identify a specific pointwise (as opposed to non-local) modular translation in BTZ-Kruskal coordinates that is analytically tractable, exploiting a connection with AdS-Rindler. This modular translation can reach the singularity.

Rigorous results on approach to thermal equilibrium, entanglement, and nonclassicality of an optical quantum field mode scattering from the elements of a non-equilibrium quantum reservoir

Rigorous derivations of the approach of individual elements of large isolated systems to a state of thermal equilibrium, starting from arbitrary initial states, are exceedingly rare. This is particularly true for quantum mechanical systems. We demonstrate here how, through a mechanism of repeated scattering, an approach to equilibrium of this type actually occurs in a specific quantum system, one that can be viewed as a natural quantum analog of several previously studied classical models. In particular, we consider an optical mode passing through a reservoir composed of a large number of sequentially-encountered modes of the same frequency, each of which it interacts with through a beam splitter. We then analyze the dependence of the asymptotic state of this mode on the assumed stationary common initial state σ of the reservoir modes and on the transmittance τ=cos⁡λ of the beam splitters. These results allow us to establish that at small λ such a mode will, starting from an arbitrary initial system state ρ, approach a state of thermal equilibrium even when the reservoir modes are not themselves initially thermalized. We show in addition that, when the initial states are pure, the asymptotic state of the optical mode is maximally entangled with the reservoir and exhibits less nonclassicality than the state of the reservoir modes.

Dependence of the stress-strain state of the upper jaw on the mechanical properties of bone tissue in patients with congenital unilateral cleft lip and palate

Резюме. Вивчення особливостей біомеханічних систем, що включають ортодонтичні конструкції та зубощелепний апарат, анатомо-топографічних характеристик вроджених дефектів та мінеральної щільності кістки, має особливе значення при лікуванні дітей із вродженими незрощеннями губи та піднебіння (ВНГП). Мета дослідження – вивчити напружено-деформований стан та визначити максимальні еквівалентні напруження у кістковій тканині верхньої щелепи при дії навантажень, спричинених активацією гвинта ортодонтичного апарату, в процесі комплексного лікування пацієнтів з однобічними ВНГП у змінному періоді прикусу залежно від мінеральної насиченості й жорсткості кістки. Матеріали і методи. Створено імітаційну комп’ютерну модель напружено-деформованого стану системи ортодонтичний апарат – кістка в заданих умовах статичного навантаження. Розділення неоднорідних за біомеханічними характеристиками біологічних структур проведено за рентгенологічною щільністю. Оцінено максимальну величину еквівалентних напружень у кістковій тканині в ділянках їх максимальної концентрації, отримані величини зіставлено із гранично-допустимими для кортикального шару кістки. Результати досліджень та їх обговорення. Силові навантаження передавались від ортодонтичного апарату на тканини щелепи. Якісно характер розподілу напружень і деформацій у різних моделях практично не залежав від жорсткості кортикальної кістки. Зі зменшенням мінеральної насиченості й, відповідно, жорсткості кісткової тканини з 8500 до 3500 МПа у відтворених моделях величина напружень на різних ділянках знижувалась на 54–62 %. Перевантаження ділянок кортикального шару може призводити до зриву адаптивно-пристосувальних механізмів, порушень процесу перебудови кістки та її руйнуванню на мікрорівні. Висновки. Встановлені закономірності свідчать про необхідність диференційованого підходу у виборі режимів активації ортодонтичних апаратів у пацієнтів із різними біомеханічними властивостями кісткової тканини незрощеної верхньої щелепи з метою запобігти виникненню ускладнень та оптимізації лікування.

Quantum Dynamics of O(3P)+HBr→OH+Br Reaction: Integral Cross Sections and Rate Constants and their Initial State Dependence.

The integral cross sections (ICSs) and rate constants (RCs) for the title reaction are calculated by means of accurate quantum wave packet method employing the recent ab initio potential energy surface developed by Peterson and co-workers. Hundreds of partial wave contributions (up to J=150) are calculated explicitly taking Coriolis coupling into account. The ICSs are found to increase monotonically with energy and their energy dependences are smooth except in the energy range below the potential energy barrier, where several resonance peaks are observed. The temperature dependences of the RCs obey in general the Arrhenius law. These behaviors manifest the dominance of abstract mechanism. Initial rotational state (ji) excitations are found to greatly enhance the reactivity starting from ji=4, while exhibiting a complicated dependence for ji<4. From Boltzmann average of the initial state specified RCs (for ji=0-15) we obtained thermal RCs which are in reasonable agreement with available experimental results.

Age-dependent coupling characteristics of bilateral frontal EEG during desflurane anesthesia.

Objectives.The purpose of this study is to investigate the age dependence of bilateral frontal electroencephalogram (EEG) coupling characteristics, and find potential age-independent depth of anesthesia monitoring indicators for the elderlies.Approach.We recorded bilateral forehead EEG data from 41 patients (ranged in 19-82 years old), and separated into three age groups: 18-40 years (n= 12); 40-65 years (n= 14), >65 years (n= 15). All these patients underwent desflurane maintained general anesthesia (GA). We analyzed the age-related EEG spectra, phase amplitude coupling (PAC), coherence and phase lag index (PLI) of EEG data in the states of awake, GA, and recovery.Main results.The frontal alpha power shows age dependence in the state of GA maintained by desflurane. Modulation index in slow oscillation-alpha and delta-alpha bands showed age dependence and state dependence in varying degrees, the PAC pattern also became less pronounced with increasing age. In the awake state, the coherence in delta, theta and alpha frequency bands were all significantly higher in the >65 years age group than in the 18-40 years age group (p< 0.05 for three frequency bands). The coherence in alpha-band was significantly enhanced in all age groups in GA (p< 0.01) and then decreased in recovery state. Notably, the PLI in the alpha band was able to significantly distinguish the three states of awake, GA and recovery (p< 0.01) and the results of PLI in delta and theta frequency bands had similar changes to those of coherence.Significance.We found the EEG coupling and synchronization between bilateral forehead are age-dependent. The PAC, coherence and PLI portray this age-dependence. The PLI and coherence based on bilateral frontal EEG functional connectivity measures and PAC based on frontal single-channel are closely associated with anesthesia-induced unconsciousness.

The abstinence from smartphone scale (ABSS-10): Psychometric properties and practical utility

In order to frame excessive smartphone use as an addiction, it is important to understand whether this behavior determines abstinence symptoms and which damaging effect it has on emotions and cognition. However, an appropriate tool to assess the presence of smartphone abstinence symptoms is still lacking. In the present study, we propose a scale that is specifically developed to assess the psychological state deriving from smartphone abstinence: The Abstinence from Smartphone Scale (ABSS-10). The aim of this work is to validate ABSS-10 and to investigate its relevance in the context of smartphone addiction. Two studies were conducted to explore ABSS-10 psychometric properties, focusing on discriminant validity, and its relationship with smartphone dependence and emotional attachment. In Study 1, university students were administered the ABSS-10 two times during a two and a half-hour long smartphone restriction period. In Study 2, the scale was administered three times during a five-hour long smartphone restriction period. General state anxiety and smartphone dependence scales were also administered. The findings reveal that ABSS-10 effectively differentiates smartphone abstinence symptoms from general state anxiety and dependence. Moreover, results show that the scale detects changes in abstinence symptoms scores during a five-hour restriction period. The scale's utility in both research and practical settings is discussed, highlighting its potential contributions to understanding the psychological dynamics of smartphone use and abstinence. The present work suggests that ABSS-10 is a robust tool for research on the psychological effects of smartphone usage.

Hospital Queues, Patient Health, and Labor Supply

Long waits for health care raise concerns about the consequences of delayed treatment. We use variation in queue congestion to estimate effects of wait time for orthopedic surgery. We do not find that longer wait times lead to increased health care utilization. However, we do find persistent reductions in labor supply: long waits increase medium to long-term work absences and permanent disability receipt. Effects are driven by individuals who are on sick leave at referral. Our results are consistent with patterns of state dependence, where extended periods of temporary disability while awaiting treatment create persistent barriers to returning to work. (JEL I11, I12, I18, J22)