Field Operators Research Articles

Characterizations of warped product pointwise semi-slant submanifolds of Sasakian manifold

A warped product submanifold, whose tangent bundle can be decomposed to two orthogonal distributions; invariant and pointwise slant, is called a warped product pointwise semi-slant submanifold. The objective of this paper is to classify warped product pointwise semi-slant submanifolds, isometrically immersed into a Sasakian manifold. Park [25] provided the (non)-existence of a warped product pointwise semi-slant submanifold in a Sasakian manifold such that the structure vector field is tangential to fibers. In contrast, we provide intriguing theorems on warped product pointwise semi-slant submanifolds in a Sasakian manifold in terms of the shape operator and tensor fields such that the structure vector field is tangential to a base manifold and each fiber is a pointwise slant submanifold.

QED in space–time varying materials

Space–time variation spoils frequency conservation and brings negative frequencies into the picture. In addition, the quantum nature of light comes to the fore in a manner not evident in static systems. Here, we explore the quantum structure of these systems; propose a Hamiltonian; show that, in the Heisenberg picture, quantum field operators evolve according to classical equations; and discuss the uniquely quantum phenomenon of photon-pair creation.

Perturbative method for mutual information and thermal entropy of scalar quantum fields

A new approach is presented to compute entropy for massless scalar quantum fields. By perturbing a skewed correlation matrix composed of field operator correlation functions, the mutual information is obtained for disjoint spherical regions of size r at separation R, including an expansion to all orders in r/R. This approach also permits a perturbative expansion for the thermal field entropy difference in the small temperature limit (T ≪ 1/r).

Hybrid team game algorithm for dynamic economic-emission electric power generation scheduling

The rising greenhouse gases, insufficient electricity production, and growing demand call for optimal thermal power generation scheduling to minimise fuel costs and emissions. Traditional optimisation methods are unable to find solutions due to non-convex objective functions and constrained convergence. Meta-heuristic techniques gain attention to address static and dynamic economic-emission generation scheduling challenges, owing to their adaptable nature and derivative-free structures. This paper proposes a Hybrid Team Game Algorithm (HTGA) that incorporates learning and exchange operators, simplex search, passing, mistake, substitution, and player within the field operators to solve the dynamic economic-emission generation scheduling (DEEPGS) of thermal units while considering multiple fuel options, valve loading effect, prohibited zone avoidance, meeting ramp-rate limits, and spinning reserve constraints. By evaluating generation scheduling at initial intervals, the forward strategy provides a solution to the dynamic EEPGS problem. A non-interactive approach uses the price penalty method to combine the objective functions, and heuristics are employed to explore feasible solutions using a replacement technique and proportional power sharing for unmet load demand. The algorithm's versatility is demonstrated across benchmark problems and electric power systems, as affirmed by Friedman and Wilcoxon's tests. Notably, HTGA requires fewer sensitive parameters, enhancing its practical applicability in addressing the DEEPGS of thermal units.

Spatial-temporal dynamics of stimulated Raman scattering: Effects of populations and two-photon detuning

A quantum theory of stimulated Raman scattering is established that takes into account the time-dependence of pump laser pulse, two-photon detuning and atomic populations, allowing the general transient and spatial propagation study of Raman memory. Heisenberg–Langevin and Maxwell equations for the collective atomic operators are solved analytically under adiabatic condition, where the electric field envelopes and the collective atomic operators vary slowly. The analytical solution of Stokes/anti-Stokes signal electric field operator is obtained. The spatial–temporal intensity of quantum signal field is studied numerically and analytically for different two-photon detunings and initial populations.

Performance Envelope of a 538-Series High-Speed Helico-Axial Pump for High-Gas-Volume-Fraction Operation

Summary Operating at high speeds can have the benefit of increasing the capability of pumps to enhance surface or downhole production of fluids with high gas volume fraction (GVF). This study presents the performance envelope of a high-speed helico-axial pump (HAP) operating at high GVFs (>80%). The ultimate aim of the physical tests was to ascertain the operating capabilities of the pump for potential scaleup to a field prototype. The HAP housing outer diameter was 5.38 in. and operated at a rotational speed of 6,000 rev/min. Air and water were the test fluids, with an average pump intake and a discharge temperature of 28°C. The fluid volume flow rates were varied while maintaining 46 psig at the HAP intake. The liquid and total intake volume flow rates varied from 128 B/D to 664 B/D and 4,941 B/D to 7,593 B/D, respectively. The corresponding dimensionless pressure boost (DPB), GVF, liquid flow coefficients (LFCs), and total flow coefficients (TFCs) were recorded. Additional parameters noted were the percentage of electric current draw to full-load motor current by the HAP motor and the percentage of electric power input to full load power to the HAP motor. The results showed that the HAP had a stable operation during the tests for intake GVF range of 91–98%. The corresponding pump DPB was in the range of 0.0138–0.0751. These values being positive indicated the capability of the HAP to boost fluid pressure even for such high intake gas content and avoid pump gas lock. The results also showed that for a given intake GVF, the HAP DPB increased with decreasing LFC. For a given LFC, the DPB decreased with increasing intake GVF. The percent electric input power to the HAP motor varied between 28% and 64% of full-load motor power. It was observed to strongly increase with decreasing LFC at a given intake GVF and very strongly decrease with increasing intake GVF at a given LFC. The associated percent electric current draw by the HAP motor was seen to vary between 24% and 53% of full-load motor current. Its variation with LFC and intake GVF was similar to those of the percent electric power input. The DPB, percent electric current, and power draw by the HAP motor variations with TFC for a given intake GVF were similar to those of the LFCs. In conclusion, the HAP demonstrated the capability to boost fluid pressure when handling high GVF flows. It is being scaled up to a field prototype to handle higher volume flow rates of high GVF gas-liquid mixtures. This study mainly highlights the method to extend the gas-handling capability of a HAP by operating it at high speeds. Optimal hydraulic design and proper conditioning of the inlet flow components were also incorporated into the HAP architecture. Expanding the HAP operating envelope to handle high-GVF flows significantly unlocks the potential for field operators to maximize hydrocarbon production from high-gas content applications. This, in turn, increases the economic bottom line from the field asset.

Some remarks on the magnetic field operators \nabla±iA and its applications

In the present paper, we give some remarks on the magnetic field operators $\nabla \pm iA$. As its applications, we study the Schr\"{o}dinger equation with a magnetic field \begin{equation*} -\Delta u+|A(x)|^{2}u+iA(x)\cdot \nabla u=\mu u+|u|^{p}u,~x\in \mathbb{R}^{N}, \end{equation*} where $u$ is a complex-valued function and $\mu\in \mathbb{R}$. When $N>2$, for $2 p+2 \frac{2N}{N-2}$ or $N=2$, for $2 p+2 +\infty$, the existence and nonexistence of minimizers of the corresponding minimization problem are given via constrained variational methods. As a by-product, the above equation admits a normalized solution. We point out that the condition ${div}A(x)=0$ plays a crucial role in our study.

Optical recursional and normalized electroosmotic magnetical Heisenberg optimistic energies

In this manuscript, we obtain optical Heisenberg normalization and recursional operators of biharmonic H n q particle for ϕ ( t q ) , ϕ ( n q ) , ϕ ( b q ) . The significance of this study is to obtain optical recursional and normalized operators of magnetic field. The aim of this study is to construct Heisenberg normalized biharmonic H n q -electroosmotic magnetical ϕ ( t q ) , ϕ ( n q ) , ϕ ( b q ) Heisenberg optimistic energies. The major conclusion of the study is microfluidic Heisenberg recursional biharmonic H n q -electroosmotic magnetical ϕ ( t q ) , ϕ ( n q ) , ϕ ( b q ) Heisenberg optimistic energies.

Controlled transport of fluid particles by microrotors in a Stokes flow using linear transfer operators

The manipulation of a collection of fluid particles in a low Reynolds number environment has several important applications. As we demonstrate in this paper, this manipulation problem is related to the scientific question of how fluid flow structures direct Lagrangian transport. We investigate this problem of directing the transport by manipulating the flow, specifically in the Stokes flow context, by controlling the strengths of two rotors fixed in space. We demonstrate a novel dynamical systems approach for this problem and apply this method to several scenarios of Stokes flow in unbounded and bounded domains. Furthermore, we show that the time-varying flow field produced by the optimal control can be understood in terms of dynamical structures such as coherent sets that define Lagrangian transport. We model the time evolution of the fluid particle density using finite-dimensional approximations of the Liouville operators for the microrotor flow fields. Using these operators, the particle transport problem is framed as an optimal control problem, which we solve numerically. This framework is then applied to the problem of transporting a blob of fluid particles in domains with different boundary conditions: free space, near to a plane wall, in a circular confinement, and the transport of two distributions of particles to a common target. These examples demonstrate the effectiveness of the proposed framework and also shed light on the effects of boundaries on the ability to achieve a desired fluid transport using a rotor-driven flow.

Scalar two-point functions at the late-time boundary of de Sitter

We calculate two-point functions of scalar fields of mass m and their conjugate momenta at the late-time boundary of de Sitter with Bunch-Davies boundary conditions, in general d + 1 spacetime dimensions. We perform the calculation using the wavefunction picture and using canonical quantization. With the latter one clearly sees how the late-time field and conjugate momentum operators are linear combinations of the normalized late-time operators αN and βN that correspond to unitary irreducible representations of the de Sitter group with well-defined inner products. The two-point functions resulting from these two different methods are equal and we find that both the autocorrelations of αN and βN and their cross correlations contribute to the late-time field and conjugate momentum two-point functions. This happens both for light scalars m<d2H\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\left(m<\\frac{d}{2}H\\right) $$\\end{document}, corresponding to complementary series representations, and heavy scalars m>d2H\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\left(m>\\frac{d}{2}H\\right) $$\\end{document}, corresponding to principal series representations of the de Sitter group, where H is the Hubble scale of de Sitter. In the special case m = 0, only the βN autocorrelation contributes to the conjugate momentum two-point function in any dimensions and we gather hints that suggest αN to correspond to discrete series representations for this case at d = 3.

Quantum field theory for coherent photons: isomorphism between Stokes parameters and spin expectation values

Stokes parameters (S) on the Poincaré sphere are very useful values to describe the polarisation state of photons. However, the fundamental principle on the nature of polarisation is not completely understood, yet, because we have no concrete consensus on how to describe spin of photons, quantum-mechanically. Here, we have considered a monochromatic coherent ray of photons, described by a many-body coherent state, and established a fundamental basis to describe the spin state of photons, in connection with a classical description based on Stokes parameters. We show that a spinor description of the coherent state is equivalent to Jones vector for polarisation states, and obtain the spin operators (Ŝ) of all components based on rotators in an SU(2) group theory. Polarisation controllers such as phase-shifters and rotators are also obtained as quantum-mechanical field operators to change the phase of the wavefunction for polarisation states. We show that the Stokes parameters are quantum-mechanical average of the spin operators, S=⟨Ŝ⟩.

Spinal Anestesi Pada Tindakan Transuretral Resection Of Prostat (TURP)

Spinal anesthesia is the choice for Transurethral Resection of Prostate (TURP) procedures. TURP is a surgical procedure performed for patients with prostatic hyperplasia. When a TURP procedure is performed, excessive fluid absorption will occur because during the procedure the injured area causes the vein to open and irrigation fluid will be absorbed. The position of the surgical procedure in the lithotomy position makes the situation worse. Spinal anesthesia helps peripheral blood collection and reduces circulatory overload, early detection of TURP syndrome and bladder perforation. In this case, the procedure was carried out on a 67 year old man with a diagnosis of benign prostate hyperplasia (BPH) with a TURP surgical procedure. The patient was composmentis, ASA III. The patient underwent spinal anesthesia with a sub arachnoid block using Bupivacaine. During TURP procedures, TURP syndrome can occur which is influenced by the use of fluid as irrigation to widen the operator's field of view. Saline fluid should be used, but because it is expensive, H2O is often used as irrigation fluid. A complication of the TURP procedure is TURP syndrome

Optimization of Targeted Differential Interferometric Measurements for Wellpads Detected by Mask Region-Based Convolutional Neural Network in the Tengiz Oilfield of the Caspian Sea Coast

Many previous studies have primarily focused on the use of deep learning for interferometric processing or separate recognition purposes rather than targeted measurements of detected wellpads. The present study centered around the integration of deep learning recognition and interferometric measurements for Tengiz oilfield wellpads. This study proposes the optimization, automation, and acceleration of targeted ground deformation wellpad monitoring. Mask Region-based Convolutional Neural Network (R-CNN)-based deep learning wellpad recognition and consequent Small Baseline Subset Synthetic Aperture Radar Interferometry (SBAS-InSAR) analyses were used for the assessment of ground deformation in the wellpads. The Mask R-CNN technique allowed us to detect 159 wells with a confidence level of more than 95%. The Mask R-CNN model achieved a precision value of 0.71 and a recall value of 0.91. SBAS-InSAR interferometric measurements identified 13 wells for Sentinel-1 (SNT1), 8 wells for COSMO-SkyMed (CSK), and 20 wells for TerraSAR-X (TSX) located within the −54–−40 mm/y class of vertical displacement (VD) velocity. Regression analyses for the annual deformation velocities and cumulative displacements (CD) of wells derived from SNT1, CSK, and TSX satellite missions showed a good agreement with R2 &gt; 95. The predictions for cumulative displacements showed that the vertical subsidence processes will continue and reach −339 mm on 31 December 2023, with increasing spatial coverage and the potential to impact a higher number of wells. The hydrological analyses in the Tengiz oilfield clearly demonstrated that water flow has been moving towards the detected hotspot of subsidence and that its accumulation will increase with increasing subsidence. This detected subsidence hotspot was observed at a crossing with a seismic fault that might always be subject to reactivation. The role of this seismic fault should also be investigated as one of the ground deformation-controlling factors, even though this area is not considered seismically active. The primary practical and scientific values of these studies were identified for the operational risk assessment and maintenance needs of oilfield and gas field operators.

Quantum de Sitter Geometry

Quantum de Sitter geometry is discussed using elementary field operator algebras in Krein space quantization from an observer-independent point of view, i.e., ambient space formalism. In quantum geometry, the conformal sector of the metric becomes a dynamical degree of freedom, which can be written in terms of a massless minimally coupled scalar field. The elementary fields necessary for the construction of quantum geometry are introduced and classified. A complete Krein–Fock space structure for elementary fields is presented using field operator algebras. We conclude that since quantum de Sitter geometry can be constructed by elementary fields operators, the geometry quantum state is immersed in the Krein–Fock space and evolves in it. The total number of accessible quantum states in the universe is chosen as a parameter of quantum state evolution, which has a relationship with the universe’s entropy. Inspired by the Wheeler–DeWitt constraint equation in cosmology, the evolution equation of the geometry quantum state is formulated in terms of the Lagrangian density of interaction fields in ambient space formalism.

Foundations of time-symmetric physics. 2. Quantum field theory

Time symmetric theory (TST), described in the first article and based on the equivalence principle of particle physics, is applied to quantum fields and time-symmetric quantum field theory is formulated. This principle is based on the Zisman-Stückelberg-Feynman interpretation, where antiparticles are described as negative energy particles moving backward in time, and generalizes it to the rest frames of such particles also moving backward in time. In TST, relativistic fields are described by complex field operators, and observables are automatically normally ordered. For this reason, at time-symmetric quantization (TSQ) of fields, the vacuum energy and charge disappear and there is no cosmological constant problem. In TST, the probabilities of states are positive, and the probability currents can have two signs depending on the direction of evolution along the time axis. The operator of interaction current is defined as the product of the probability current and the matrix of interaction constants. Applications of TST to the Standard Model fields and graviton field are considered. In TSQ correctly describes the observable effects, since in terms of ordinary time it leads to a standard diagram technique, transforming mathematical recipes of the latter into logical consequences of physical principles.

Model λ(φ 2n )4, n ≥ 2 quantum field theory: A nonstandard approach based on nonstandard pointwise-defined quantum fields

A new non-Archimedean approach to interacted quantum fields is presented. In proposed approach, a field operator φ(x, t), no longer a standard tempered operator-valued distribution, but a non-classical operator-valued function. We prove using this novel approach that the quantum field theory with Hamiltonian P(φ)4 exists and that the corresponding C* - algebra of bounded observables satisfies all the Haag-Kastler axioms except Lorentz covariance. We prove that the λ(φ 2n )4, n ≥ 2 quantum field theory models are Lorentz covariant.

Evaluation of tieback developments for marginal oil fields with timing flexibility

The average size of new oil discoveries on the Norwegian Continental Shelf (NCS) is steadily decreasing. As standalone developments are often not economically viable for marginal fields, tiebacks to existing production facilities are considered in many cases. At the same time, many production facilities in mature production areas have spare capacity due to depleted reservoirs. In this paper we evaluate tieback development concepts for a marginal field having the choice between two hosts with different characteristics. We develop a model that allows to (1) evaluate the tieback development concepts; (2) determine the optimal choice of host facility for the field operator; and (3) optimize the timing of development taking into account oil, gas price and CAPEX uncertainty using a real options approach. In order to be able to reflect how the capacity constraints of a host affects the production potential of the field over time, we incorporate a production optimization model as part of the methodology. We apply the model to a real case on the NCS. We identify characteristics that drive the optimal choice of hosts. Specifically, we show how lifetime extension, reduction of CAPEX and additional spare capacity individually and in combination affect the competitiveness of one host over another therewith, providing valuable insight for tariff negotiations and portfolio planning. Apart from that we find that timing flexibility is of high importance in case of high downside risk. This makes our approach particularly relevant for marginal oil field development which are often characterized by prominent uncertainties.

The Evolving Landscape of Oil and Gas Chemicals: Convergence of Artificial Intelligence and Chemical-Enhanced Oil Recovery in the Energy Transition Toward Sustainable Energy Systems and Net-Zero Emissions

Chemical-enhanced oil recovery (EOR) is a field of study that can gain significantly from artificial intelligence (AI), addressing uncertainties such as mobility control, interfacial tension reduction, wettability alteration, and emulsifications. The primary objective of this paper is to introduce an integrated framework for AI and chemical EOR for energy harvest operations. Central emphasis is placed on the energy transition, with the aim of expediting the development of cleaner energy harvesting systems and attaining the goal of net-zero emission. To do so, we present how the energy transition is changing the manufacturing of the chemicals for EOR application. For this, the uncertainty associated with materials' design and critical role of the simulators for transferring the laboratory experiences into full-field implementations is discussed. The concept of digitalization and its impact on energy companies are highlighted. The role of digital twin in simulators integration is discussed, emphasizing how increased data access can help design more tolerant chemicals for harsh reservoir environments using real-time data. Also, we discuss how the chemical suppliers, research institutes, startups, and field operators can benefit from self-leaning and robotic laboratories for chemicals manufacturing. Moreover, this paper explores how including AI perspectives can improve our understanding of developing chemical formulations by blending hybrid capabilities. This approach contributes to making energy production more sustainable and aligning with the goal of zero emissions. A workflow is presented to demonstrate how the integration of AI and chemical EOR can be used for both hydrocarbon production and other energy transition operations, such as carbon capture, utilization and storage, hydrogen storage, and geothermal reservoirs. The outcome of this paper stands as a pioneering effort that uniquely addresses these challenges for both academia and the industry and can open many additional doors and identify topics requiring further investigations.

Integrated building fault detection and diagnosis using data modeling and Bayesian networks

Heating, ventilation, and air-conditioning (HVAC) equipment faults and operational errors result in comfort issues and waste of energy in buildings. An Automatic Fault Detection and Diagnosis (AFDD) tool could help facility managers fix comfort and energy issues more efficiently, by identifying the most probable root causes. Existing AFDD methods mostly focus on equipment-level fault detection and diagnostics; almost no attention is given to building level fault diagnosis, considering inter-dependency between equipment through the energy distribution chain. In this work we propose a methodology to automatically derive a Bayesian network from HVAC system topology description such as Haystack. This Bayesian network models and estimates the state of all elements in the system, helping users to identify the most probable root fault. As it is able to ingest evidence from any source (field data, operators, or other models) and is capable of updating its estimates when new evidence is delivered, such a tool could have a great potential to be used interactively on the field. We applied the proposed methodology on simulated and real-world buildings and present in this paper one specific case.

Vacuum Currents for a Scalar Field in Models with Compact Dimensions

This paper presents a review of investigations into the vacuum expectation value of the current density for a charged scalar field in spacetimes that hold toroidally compactified spatial dimensions. As background geometries, the locally Minkowskian (LM), locally de Sitter (LdS), and locally anti-de Sitter (LAdS) spacetimes are considered. Along compact dimensions, quasi-periodicity conditions are imposed on the field operator and the presence of a constant gauge field is assumed. The vacuum current has nonzero components along the compact dimensions only. Those components are periodic functions of the magnetic flux enclosed in compact dimensions, with a period that is equal to the flux quantum. For LdS and LAdS geometries, and for small values of the length of a compact dimension, compared with the curvature radius, the leading term in the expansion of the the vacuum current along that dimension coincides with that for LM bulk. In this limit, the dominant contribution to the mode sum for the current density comes from the vacuum fluctuations with wavelengths smaller to those of the curvature radius; additionally, the influence of the gravitational field is weak. The effects of the gravitational field are essential for lengths of compact dimensions that are larger than the curvature radius. In particular, instead of the exponential suppression of the current density in LM bulk, one can obtain a power law decay in the LdS and LAdS spacetimes.