Search

In quantum mechanics, randomness is postulated as a separate axiom. De Broglie's theory allows one to reproduce quantum phenomena from completely deterministic formalism. But the question of the quantum randomness emergency in the de Broglie-Bohm theory needs special attention. In the work [G. Tastevin, F. Lalo\"e, Comptes Rendus. Physique, 2021, 22, 1, pp. 99-116], it was shown that it arises as a result of the device microscopic state influence on the measurement result. In our work, we investigate the genesis of the quantum randomness in the de Broglie's theory in more details. Namely, we investigate the target system and the device behaviour in the decoherence process and model the measurement of canonical-conjugate observables. We propose a thought experiment which tests the opportunity of the information transition using beable-parameters violating the uncertainty relation. We show that in the measurement process, the strong stochastic fluctuations of beable parameters arise randomising the system in accordance with the uncertainty relation. Nevertheless, we find anomalous models of measurement in which these fluctuations can be neglected. These special models require further investigation., Comment: 8 pages (2 columns), 5 figures

We present a theoretical study of an exciton-polariton annular microcavity with an additional quasiperiodic structure along the ring which is implemented in the form of a bicosine dependence. We demonstrate that for a sufficiently strong quasiperiodic modulation, the microcavity features a sharp mobility edge separating a cluster of localized states from the rest of the spectrum consisting of states extended over the whole ring. Localized modes can be excited using a resonant pump whose topological charge determines the phase distribution of excited patterns. Repulsive polariton interactions make the resonance peaks distinctively asymmetric and enable the formation of multistable states which feature the attractor-like dynamical behavior \rev{and hysteresis}. We also demonstrate that the localized states can be realized in a biannular cavity that consists of two rings, each having periodic modulation, such that the periods of two modulations are different., Comment: 8 pages, 6 figures; to appear in Phys. Rev. B

We present first theoretical predictions for various observables related to the $\bar B_d \to \mu^+ \mu^- e^+ e^-$ decay within the framework of the Standard Model. Our study encompasses the branching ratios, differential distributions, and forward-backward leptonic asymmetries. To obtain these predictions, we account for several contributions: resonance contribution from $\rho(770)$ and significant contribution $\omega(782)$; contributions from four charmonium resonances: $\psi(3770)$, $\psi(4040)$, $\psi(4160)$, and $\psi(4415)$; additional contributions from the "tails" of $J/\psi$ and $\psi(2S)$ resonances; non-resonant contributions arising from virtual photon emission by a $b$-quark of $B_d$ meson, bremsstrahlung, and weak annihilation. In our calculations we employ the model of vector meson dominance (VMD) to assess the resonance contributions accurately. We provide the predictions for the branching ratio of the $\bar B_d \to \mu^+ \mu^- e^+ e^-$ decay both with and without the resonant contribution from $\omega(782)$., Comment: arXiv admin note: text overlap with arXiv:2112.06093

Fast multi-phase processes in methane hydrate-bearing samples are challenging for micro-CT quantitative study because of complex tomographic data analysis involving time-consuming segmentation procedures. This is due to the sample multi-scale structure changing in time, low X-ray attenuation and phase contrast between solid and fluid materials, as well as large amount of data acquired during dynamic processes. We propose a hybrid approach for automatic segmentation of tomographic data from time-resolved imaging of methane gas-hydrate formation in sandy granular media. First, we use an optimized 3D U-net neural network to perform segmentation of mineral grains that are characterized by low contrast to the surrounding pore brine-saturated phases. Then, we perform statistical clustering based on the Gaussian mixture model for separating the pore-space phases that are characterized by gray-level instabilities caused by dynamic processes during hydrate formation. The proposed approach was used for segmenting several hundred gigabytes of data acquired during an in-situ tomographic experiment at a synchrotron. Automatic segmentation allowed for studying properties of the hydrate growth in pores, as well as dynamic processes such as the incremental pore-brine flow and redistribution.

In the framework of the Standard Model we present new theoretical predictions for the branching ratios, double and single differential distributions and forward -- backward leptonic asymmetries for the $\bar B_s \to \mu^+ \mu^- e^+ e^-$ decay. In our consideration we take into account the $\phi(1020)$ -- resonance contribution; the main contributions of four charmonium resonances : $\psi(3770)$, $\psi(4040)$, $\psi(4160)$ and $\psi(4415)$; $u\bar{u}$ -- resonant contribution from $\rho(770)$ and $\omega(782)$; tails contributions from $J/\psi$ and $\psi(2S)$ resonances; non -- resonant contribution of the $b\,\bar{b}$ - pairs, bremsstrahlung and the contribution of the weak annihilation. We provide the prediction for the branching ratio of $\bar B_s \to \mu^+ \mu^- e^+ e^-$ decay with and without the $\phi(1020)$ -- resonance contribution. We use the model of vector meson dominance (VMD) for calculation of resonances contributions and take into account all substantive terms in $\bar B_s \to \mu^+ \mu^- e^+ e^-$ amplitude that was not considered in the previously papers.

This paper presents a novel way to predict options price for one day in advance, utilizing the method of Quasi-Reversibility for solving the Black-Scholes equation. The Black-Scholes equation solved forwards in time with Tikhonov regularization as an ill-posed problem allows for extrapolation of option prices. This provides high-accuracy results, which can be further improved by applying Neural Network Machine Learning to the solution of the Black-Scholes equation as well as initial and boundary conditions and implied volatility. Using historical option and stock price data the results obtained from the method of Quasi-Reversibility and Machine Learning method are compared in terms of accuracy, precision and recall. It is shown that these methods can be applied to the real-world trading within a variety of trading strategies.

In low-power wide-area networks (LPWANs), various trade-offs among the bandwidth, data rates, and energy per bit have different effects on the quality of service under different propagation conditions (e.g. fading and multipath), interference scenarios, multi-user requirements, and design constraints. Such compromises, and the manner in which they are implemented, further affect other technical aspects, such as system's computational complexity and power efficiency. At the same time, this difference in trade-offs also adds to the technical flexibility in addressing a broader range of IoT applications. This paper addresses a physical layer LPWAN approach based on the Aggregate Spread Pulse Modulation (ASPM) and provides a brief assessment of its properties in additive white Gaussian noise (AWGN) channel. In the binary ASPM the control of the quality of service is performed through the change in the spectral efficiency, i.e., the data rate at a given bandwidth. Implementing M-ary encoding in ASPM further enables controlling service quality through changing the energy per bit (in about an order of magnitude range) as an additional trade-off parameter. Such encoding is especially useful for improving the ASPM's energy per bit performance, thus increasing its range and overall energy efficiency, and making it more attractive for use in LPWANs for IoT applications., Comment: 7 pages, 7 figures

It was proposed by Klibanov a new empirical mathematical method to work with the Black-Scholes equation. This equation is solved forwards in time to forecast prices of stock options. It was used the regularization method because of ill-posed problems. Uniqueness, stability and convergence theorems for this method are formulated. For each individual option, historical data is used for input. The latter is done for two hundred thousand stock options selected from the Bloomberg terminal of University of Washington. It used the index Russell 2000. The main observation is that it was demonstrated that technique, combined with a new trading strategy, results in a significant profit on those options. On the other hand, it was demonstrated the trivial extrapolation techniques results in much lesser profit on those options. This was an experimental work. The minimization process was performed by Hyak Next Generation Supercomputer of the research computing club of University of Washington. As a result, it obtained about 50,000 minimizers. The code is parallelized in order to maximize the performance on supercomputer clusters. Python with the SciPy module was used for implementation. You may find minimizers in the source package that is available on GitHub. Chapter 7 is dedicated to application of machine learning. We were able to improve our results of profitability using minimizers as new data. We classified the minimizer's set to filter for the trading strategy. All results are available on GitHub.

In traditional spread-spectrum techniques, a wideband transmit signal is obtained by modulating a wideband carrier by a narrowband signal containing a relatively low-rate message. In the receiver, the respective demodulation/despreading restores the information-carrying narrowband signal. In this paper, we introduce an alternative approach, where the low-rate information is encoded directly into a wideband waveform of a given bandwidth, without physical "spreading" of the carrier's frequency. The main advantages of this approach lie in extended options for encoding the information, and in retaining a reversible control over the temporal and amplitude structures of the modulating wideband waveforms. Significant "excess bandwidth" (over that needed to carry the information) enables us to use allpass filters to manage statistical properties and time-domain appearances of these waveforms without changing their spectral composition. For example, a mixture of transmitted waveforms can be shaped as a low-crest-factor signal (e.g. to reduce the burden on the power amplifier), and/or made statistically indistinguishable from Gaussian noise (e.g. for covert transmissions and physical layer steganography), while the selected components of the received waveform can be transformed into high-crest-factor pulse trains suitable for multiplexing and/or low-SNR communications. Further, control over the temporal and amplitude structures of wideband waveforms carrying low-rate information enables effective use of nonlinear filtering techniques. Such techniques can be employed for robust real-time asynchronous extraction of the information, as well as for separation of wideband signal components with identical spectral content from each other. This can facilitate development of a large variety of low-SNR and covert communication configurations., Comment: 16 pages, 24 figures. arXiv admin note: substantial text overlap with arXiv:2005.00734, arXiv:2004.13610

In contrast to other spread-spectrum techniques, wideband pulse trains with relatively low pulse arrival rates may be considered unsuitable for covert communications. The high crest factor of such trains can be extremely burdensome for the transmitter hardware, and it makes the pulse trains easily detectable even at very low signal-to-noise ratios. In addition, it may appear that sharing the wideband channel by multiple users would require explicit allocation of the pulse arrival times for each sub-channel, which would be impractical in most cases. On the other hand, messaging by wideband pulse trains has many appealing features. Among those are the ease of synchronous as well as asynchronous pulse detection, and on-the-fly channel reconfigurability (e.g. changing the spreading factor). Favorably, the crest factor of a pulse train, as well as its apparent temporal and amplitude structure, can be easily, and reversibly, controlled by simple linear filtering. For example, a transmitted pulse train can be made statistically indistinguishable from the Gaussian component of the channel noise (e.g. the thermal noise) observed in the same spectral band, while the received signal will be the designed high-crest-factor wideband pulse train. In this paper, we utilize the so-called pulse pileup effect to perform such reversible control of the pulse train structure, enabling a wider use of this approach for synthesis of robust low-SNR covert communication links. We place a particular focus on the synchronous pulse detection in the receiver, that provides a better utilization of the channel spectrum., Comment: 8 pages, 11 figures. arXiv admin note: text overlap with arXiv:2004.13610

We outline an approach to physical-layer steganography where the transmitted low-power stego messages are statistically indistinguishable from the Gaussian component of the channel noise (e.g. the thermal noise) observed in the same spectral band, and thus the channel noise itself serves as an effective cover signal. We also demonstrate how the apparent spectral and temporal properties of transmitted additional, higher-power cover signals (including those using the existing communication protocols) can be made to match those of the low-power stego payload and the Gaussian noise, providing extra layers of obfuscation for both the cover and the stego messages. We further illustrate how a specific combination of linear and nonlinear filtering can be used for effective separation of the cover, payload, and/or "friendly jamming" signals even when all transmissions have essentially the same spectral characteristics as well as temporal and amplitude structures, and when there are no explicit differences in the spectral and/or temporal allocations for the cover and the stego messages., Comment: 20 pages, 18 figures

A methane line list for the HITEMP spectroscopic database, covering 0-13,400 cm$^{-1}$ ($>$746 nm), is presented. To create this compilation, ab initio line lists of $^{12}$CH$_{4}$ from Rey et al. (2017) ApJ, 847, 105 (provided at separate temperatures in the TheoReTS information system), are now combined with HITRAN2016 methane data to produce a single line list suitable for high-temperature line-by-line calculations up to 2000 K. An effective-temperature interpolation model was created in order to represent continuum-like features at any temperature of interest. This model is advantageous to previously-used approaches that employ so-called ``super-lines'', which are suitable only at a given temperature and require separate line lists for different temperatures. The resultant HITEMP line list contains $\sim$32 million lines and is significantly more flexible than alternative line lists of methane, while accuracy required for astrophysical or combustion applications is retained. Comparisons against experimental observations of methane absorption at high temperatures have been used to demonstrate the accuracy of the new work. The line list includes both strong lines and quasi-continuum features and is provided in the common user-friendly HITRAN/HITEMP format, making it the most practical methane line list for radiative transfer modeling at high-temperature conditions., Comment: 25 pages, 12 figures, submitted to the Astrophysical Journal Supplement Series

Robust fencing is an essential component of intermittently nonlinear filtering for mitigation of outlier interference. In such filtering, the upper and the lower fences establish a robust range that excludes noise outliers while including the signal of interest and the non-outlier noise. Then, the outlier values are replaced with those in mid-range. To increase the effectiveness of outlier noise identification, and to minimize the false negatives, the fences need to be both tight and robust to outlier noise. On the other hand, to minimize the false positives and to avoid the detrimental effects, such as instabilities and excessive distortions, often associated with nonlinear filtering, the fences need to be inclusive, so that the signal of interest and the non-outlier noise remain within the fences. Quantile Tracking Filters (QTFs) are an appealing choice for such robust fencing in intermittently nonlinear filtering, as QTFs are analog filters suitable for wideband real-time processing of continuous-time signals and are easily implemented in analog circuitry. Further, their numerical computations are O(1) per output value in both time and storage, which also enables their high-rate digital implementations in real time. In this paper, we first provide a brief general discussion of the outlier noise and its mitigation by intermittently nonlinear filters. We then focus on the basic properties of the QTF-based fencing, discuss the approaches to choosing its parameters, and illustrate the use of the QTF fencing for various types of the signal+noise mixtures. We also demonstrate how the Complementary Intermittently Nonlinear Filtering (CINF) arrangements allow us to increase the tightness and robustness of the QTF fencing, while preserving its inclusivity, and to enable the mitigation of outlier noise obscured by high-amplitude non-outlier signals such as the signal of interest itself., Comment: 12 pages, 17 figures