Computational science

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Computational_science 

Computational science, also known as scientific computing or scientific computation (SC), is a field in mathematics that uses advanced computing capabilities to understand and solve complex problems. It is an area of science that spans many disciplines, but at its core, it involves the development of models and simulations to understand natural systems.

• Algorithms (numerical and non-numerical): mathematical models, computational models, and computer simulations developed to solve science (e.g., biological, physical, and social), engineering, and humanities problems
• Computer hardware that develops and optimizes the advanced system hardware, firmware, networking, and data management components needed to solve computationally demanding problems
• The computing infrastructure that supports both the science and engineering problem solving and the developmental computer and information science

In practical use, it is typically the application of computer simulation and other forms of computation from numerical analysis and theoretical computer science to solve problems in various scientific disciplines. The field is different from theory and laboratory experiments, which are the traditional forms of science and engineering. The scientific computing approach is to gain understanding through the analysis of mathematical models implemented on computers. Scientists and engineers develop computer programs and application software that model systems being studied and run these programs with various sets of input parameters. The essence of computational science is the application of numerical algorithms and computational mathematics. In some cases, these models require massive amounts of calculations (usually floating-point) and are often executed on supercomputers or distributed computing platforms.

The computational scientist

Ways to study a system

The term computational scientist is used to describe someone skilled in scientific computing. Such a person is usually a scientist, an engineer, or an applied mathematician who applies high-performance computing in different ways to advance the state-of-the-art in their respective applied disciplines in physics, chemistry, or engineering.

Computational science is now commonly considered a third mode of science, complementing and adding to experimentation/observation and theory (see image on the right). Here, one defines a system as a potential source of data, an experiment as a process of extracting data from a system by exerting it through its inputs and a model (M) for a system (S) and an experiment (E) as anything to which E can be applied in order to answer questions about S. A computational scientist should be capable of:

• recognizing complex problems
• adequately conceptualizing the system containing these problems
• designing a framework of algorithms suitable for studying this system: the simulation
• choosing a suitable computing infrastructure (parallel computing/grid computing/supercomputers)
• hereby, maximizing the computational power of the simulation
• assessing to what level the output of the simulation resembles the systems: the model is validated
• adjusting the conceptualization of the system accordingly
• repeat the cycle until a suitable level of validation is obtained: the computational scientist trusts that the simulation generates adequately realistic results for the system under the studied conditions

Substantial effort in computational sciences has been devoted to developing algorithms, efficient implementation in programming languages, and validating computational results. A collection of problems and solutions in computational science can be found in Steeb, Hardy, Hardy, and Stoop (2004).

Philosophers of science addressed the question to what degree computational science qualifies as science, among them Humphreys and Gelfert. They address the general question of epistemology: how does gain insight from such computational science approaches? Tolk uses these insights to show the epistemological constraints of computer-based simulation research. As computational science uses mathematical models representing the underlying theory in executable form, in essence, they apply modeling (theory building) and simulation (implementation and execution). While simulation and computational science are our most sophisticated way to express our knowledge and understanding, they also come with all constraints and limits already known for computational solutions.

Applications of computational science

Problem domains for computational science/scientific computing include:

Predictive computational science

Predictive computational science is a scientific discipline concerned with the formulation, calibration, numerical solution, and validation of mathematical models designed to predict specific aspects of physical events, given initial and boundary conditions, and a set of characterizing parameters and associated uncertainties. In typical cases, the predictive statement is formulated in terms of probabilities. For example, given a mechanical component and a periodic loading condition, “the probability is (say) 90% that the number of cycles at failure (Nf) will be in the interval N1<Nf<N2”.

Urban complex systems

In 2018, over half the world's population lives in cities. By 2050, the United Nations estimates, 68% of the world's population will be urban. This urban growth is focused in the urban populations of developing countries where city dwellers will more than double, increasing from 2.5 billion in 2009 to almost 5.2 billion in 2050. Cities are massively complex systems created by humans, made up of humans, and governed by humans. Trying to predict, understand and somehow shape the development of cities in the future requires complex thinking and computational models and simulations to help mitigate challenges and possible disasters. The focus of research in urban complex systems is, through modeling and simulation, to build a greater understanding of city dynamics and help prepare for the coming urbanization.

Computational finance

Main article: Computational finance

In financial markets, huge volumes of interdependent assets are traded by a large number of interacting market participants in different locations and time zones. Their behavior is of unprecedented complexity and the characterization and measurement of the risk inherent to this highly diverse set of instruments is typically based on complicated mathematical and computational models. Solving these models exactly in closed form, even at a single instrument level, is typically not possible, and therefore we have to look for efficient numerical algorithms. This has become even more urgent and complex recently, as the credit crisis has clearly demonstrated the role of cascading effects going from single instruments through portfolios of single institutions to even the interconnected trading network. Understanding this requires a multi-scale and holistic approach where interdependent risk factors such as market, credit, and liquidity risk are modeled simultaneously and at different interconnected scales.

Computational biology

Main article: Computational biology

Exciting new developments in biotechnology are now revolutionizing biology and biomedical research. Examples of these techniques are high-throughput sequencing, high-throughput quantitative PCR, intra-cellular imaging, in-situ hybridization of gene expression, three-dimensional imaging techniques like Light Sheet Fluorescence Microscopy, and Optical Projection (micro)-Computer Tomography. Given the massive amounts of complicated data that is generated by these techniques, their meaningful interpretation, and even their storage, form major challenges calling for new approaches. Going beyond current bioinformatics approaches, computational biology needs to develop new methods to discover meaningful patterns in these large data sets. Model-based reconstruction of gene networks can be used to organize the gene expression data in a systematic way and to guide future data collection. A major challenge here is to understand how gene regulation is controlling fundamental biological processes like biomineralization and embryogenesis. The sub-processes like gene regulation, organic molecules interacting with the mineral deposition process, cellular processes, physiology, and other processes at the tissue and environmental levels are linked. Rather than being directed by a central control mechanism, biomineralization and embryogenesis can be viewed as an emergent behavior resulting from a complex system in which several sub-processes on very different temporal and spatial scales (ranging from nanometer and nanoseconds to meters and years) are connected into a multi-scale system. One of the few available options to understand such systems is by developing a multi-scale model of the system.

Complex systems theory

Main article: Complex systems

Using information theory, non-equilibrium dynamics, and explicit simulations, computational systems theory tries to uncover the true nature of complex adaptive systems.

Computational science in engineering

Main article: Computational engineering

Computational science and engineering (CSE) is a relatively new discipline that deals with the development and application of computational models and simulations, often coupled with high-performance computing, to solve complex physical problems arising in engineering analysis and design (computational engineering) as well as natural phenomena (computational science). CSE has been described as the "third mode of discovery" (next to theory and experimentation). In many fields, computer simulation is integral and therefore essential to business and research. Computer simulation provides the capability to enter fields that are either inaccessible to traditional experimentation or where carrying out traditional empirical inquiries is prohibitively expensive. CSE should neither be confused with pure computer science, nor with computer engineering, although a wide domain in the former is used in CSE (e.g., certain algorithms, data structures, parallel programming, high-performance computing), and some problems in the latter can be modeled and solved with CSE methods (as an application area).

Methods and algorithms

Algorithms and mathematical methods used in computational science are varied. Commonly applied methods include:

• Computer algebra, including symbolic computation in fields such as statistics, equation solving, algebra, calculus, geometry, linear algebra, tensor analysis (multilinear algebra), optimization
• Numerical analysis, including Computing derivatives by finite differences
  • Application of Taylor series as convergent and asymptotic series
  • Computing derivatives by Automatic differentiation (AD)
  • Finite element method for solving PDEs
  • High order difference approximations via Taylor series and Richardson extrapolation
  • Methods of integration on a uniform mesh: rectangle rule (also called midpoint rule), trapezoid rule, Simpson's rule
  • Runge–Kutta methods for solving ordinary differential equations
  • Newton's method
• Discrete Fourier transform
• Monte Carlo methods
• Numerical linear algebra, including decompositions and eigenvalue algorithms
• Linear programming
• Branch and cut
• Branch and bound
• Molecular dynamics, Car–Parrinello molecular dynamics
• Space mapping
• Time stepping methods for dynamical systems

Historically and today, Fortran remains popular for most applications of scientific computing.Other programming languages and computer algebra systems commonly used for the more mathematical aspects of scientific computing applications include GNU Octave, Haskell, Julia, Maple, Mathematica, MATLAB, Python (with third-party SciPy library), Perl (with third-party PDL library), R, Scilab, and TK Solver. The more computationally intensive aspects of scientific computing will often use some variation of C or Fortran and optimized algebra libraries such as BLAS or LAPACK. In addition, parallel computing is heavily used in scientific computing to find solutions of large problems in a reasonable amount of time. In this framework, the problem is either divided over many cores on a single CPU node (such as with OpenMP), divided over many CPU nodes networked together (such as with MPI), or is run on one or more GPUs (typically using either CUDA or OpenCL).

Computational science application programs often model real-world changing conditions, such as weather, airflow around a plane, automobile body distortions in a crash, the motion of stars in a galaxy, an explosive device, etc. Such programs might create a 'logical mesh' in computer memory where each item corresponds to an area in space and contains information about that space relevant to the model. For example, in weather models, each item might be a square kilometer; with land elevation, current wind direction, humidity, temperature, pressure, etc. The program would calculate the likely next state based on the current state, in simulated time steps, solving differential equations that describe how the system operates, and then repeat the process to calculate the next state.

Conferences and journals

In 2001, the International Conference on Computational Science (ICCS) was first organized. Since then, it has been organized yearly. ICCS is an A-rank conference in CORE classification.

The Journal of Computational Science published its first issue in May 2010. The Journal of Open Research Software was launched in 2012. The ReScience C initiative, which is dedicated to replicating computational results, was started on GitHub in 2015.

Education

At some institutions, a specialization in scientific computation can be earned as a "minor" within another program (which may be at varying levels). However, there are increasingly many bachelor's, master's, and doctoral programs in computational science. The joint degree program master program computational science at the University of Amsterdam and the Vrije Universiteit in computational science was first offered in 2004. In this program, students:

• learn to build computational models from real-life observations;
• develop skills in turning these models into computational structures and in performing large-scale simulations;
• learn theories that will give a firm basis for the analysis of complex systems;
• learn to analyze the results of simulations in a virtual laboratory using advanced numerical algorithms.

George Mason University was one of the early pioneers first offering a multidisciplinary doctorate Ph.D. program in Computational Sciences and Informatics in 1992 that focused on a number of specialty areas, including bioinformatics, computational chemistry, earth systems, and global changes, computational mathematics, computational physics, space sciences, and computational statistics.^{[citation needed]}

The School of Computational and Integrative Sciences, Jawaharlal Nehru University (erstwhile School of Information Technology) also offers a vibrant master's science program for computational science with two specialties: Computational Biology and Complex Systems.

Related fields

• Bioinformatics
• Car–Parrinello molecular dynamics
• Cheminformatics
• Chemometrics
• Computational archaeology
• Computational astrophysics
• Computational biology
• Computational chemistry
• Computational materials science
• Computational economics
• Computational electromagnetics
• Computational engineering
• Computational finance
• Computational fluid dynamics
• Computational forensics
• Computational geophysics
• Computational history
• Computational informatics
• Computational intelligence
• Computational law
• Computational linguistics
• Computational mathematics
• Computational mechanics
• Computational neuroscience
• Computational particle physics
• Computational physics
• Computational sociology
• Computational statistics
• Computational sustainability
• Computer algebra
• Computer simulation
• Financial modeling
• Geographic information system (GIS)
• High-performance computing
• Machine learning
• Network analysis

Electronic oscillator

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Electronic_oscillator 

 

A popular op-amp relaxation oscillator.

An electronic oscillator is an electronic circuit that produces a periodic, oscillating electronic signal, often a sine wave or a square wave or a triangle wave. Oscillators convert direct current (DC) from a power supply to an alternating current (AC) signal. They are widely used in many electronic devices ranging from simplest clock generators to digital instruments (like calculators) and complex computers and peripherals etc. Common examples of signals generated by oscillators include signals broadcast by radio and television transmitters, clock signals that regulate computers and quartz clocks, and the sounds produced by electronic beepers and video games.

Oscillators are often characterized by the frequency of their output signal:

• A low-frequency oscillator (LFO) is an electronic oscillator that generates a frequency below approximately 20 Hz. This term is typically used in the field of audio synthesizers, to distinguish it from an audio frequency oscillator.
• An audio oscillator produces frequencies in the audio range, about 16 Hz to 20 kHz.
• An RF oscillator produces signals in the radio frequency (RF) range of about 100 kHz to 100 GHz.

In AC power supplies, an oscillator that produces AC power from a DC supply is usually called an inverter. Before the advent of diode-based rectifiers, an electromechanical device that similarly converted AC power to DC was called a converter, though the term is now used more commonly to refer to DC-DC buck converters.

There are two main types of electronic oscillator – the linear or harmonic oscillator and the nonlinear or relaxation oscillator.

Crystal oscillators are ubiquitous in modern electronics and produce frequencies from 32 kHz to over 150 MHz, with 32 kHz crystals commonplace in time keeping and the higher frequencies commonplace in clock generation and RF applications.

1 MHz electronic oscillator circuit which uses the resonant properties of an internal quartz crystal to control the frequency. Provides the clock signal for digital devices such as computers.

Harmonic oscillators

Block diagram of a feedback linear oscillator; an amplifier A with its output v_o fed back into its input v_f through a filter, β(jω).

The harmonic, or linear, oscillator produces a sinusoidal output. There are two types:

Feedback oscillator

The most common form of linear oscillator is an electronic amplifier such as a transistor or operational amplifier connected in a feedback loop with its output fed back into its input through a frequency selective electronic filter to provide positive feedback. When the power supply to the amplifier is switched on initially, electronic noise in the circuit provides a non-zero signal to get oscillations started. The noise travels around the loop and is amplified and filtered until very quickly it converges on a sine wave at a single frequency.

Feedback oscillator circuits can be classified according to the type of frequency selective filter they use in the feedback loop:

• In an RC oscillator circuit, the filter is a network of resistors and capacitors. RC oscillators are mostly used to generate lower frequencies, for example in the audio range. Common types of RC oscillator circuits are the phase shift oscillator and the Wien bridge oscillator. LR oscillators, using inductor and resistor filters also exist, however they are much less common due to the required size of an inductor to achieve a value appropriate for use at lower frequencies.

• In an LC oscillator circuit, the filter is a tuned circuit (often called a tank circuit) consisting of an inductor (L) and capacitor (C) connected together, which acts as a resonator. Charge flows back and forth between the capacitor's plates through the inductor, so the tuned circuit can store electrical energy oscillating at its resonant frequency. The amplifier adds power to compensate for resistive energy losses in the circuit and supplies the power for the output signal. LC oscillators are often used at radio frequencies, when a tunable frequency source is necessary, such as in signal generators, tunable radio transmitters and the local oscillators in radio receivers. Typical LC oscillator circuits are the Hartley, Colpitts and Clapp circuits.

Two common LC oscillator circuits, the Hartley and Colpitts oscillators

• In a crystal oscillator circuit the filter is a piezoelectric crystal (commonly a quartz crystal). The crystal mechanically vibrates as a resonator, and its frequency of vibration determines the oscillation frequency. Crystals have a very high Q-factor and also better temperature stability than tuned circuits, so crystal oscillators have much better frequency stability than LC or RC oscillators. Crystal oscillators are the most common type of linear oscillator, used to stabilize the frequency of most radio transmitters, and to generate the clock signal in computers and quartz clocks. Crystal oscillators often use the same circuits as LC oscillators, with the crystal replacing the tuned circuit; the Pierce oscillator circuit is also commonly used. Quartz crystals are generally limited to frequencies of 30 MHz or below. Other types of resonators, dielectric resonators and surface acoustic wave (SAW) devices, are used to control higher frequency oscillators, up into the microwave range. For example, SAW oscillators are used to generate the radio signal in cell phones.

Negative-resistance oscillator

(left) Typical block diagram of a negative resistance oscillator. In some types the negative resistance device is connected in parallel with the resonant circuit. (right) A negative-resistance microwave oscillator consisting of a Gunn diode in a cavity resonator. The negative resistance of the diode excites microwave oscillations in the cavity, which radiate out the aperture into a waveguide.

In addition to the feedback oscillators described above, which use two-port amplifying active elements such as transistors and operational amplifiers, linear oscillators can also be built using one-port (two terminal) devices with negative resistance, such as magnetron tubes, tunnel diodes, IMPATT diodes and Gunn diodes. Negative-resistance oscillators are usually used at high frequencies in the microwave range and above, since at these frequencies feedback oscillators perform poorly due to excessive phase shift in the feedback path.

In negative-resistance oscillators, a resonant circuit, such as an LC circuit, crystal, or cavity resonator, is connected across a device with negative differential resistance, and a DC bias voltage is applied to supply energy. A resonant circuit by itself is "almost" an oscillator; it can store energy in the form of electronic oscillations if excited, but because it has electrical resistance and other losses the oscillations are damped and decay to zero. The negative resistance of the active device cancels the (positive) internal loss resistance in the resonator, in effect creating a resonator with no damping, which generates spontaneous continuous oscillations at its resonant frequency.

The negative-resistance oscillator model is not limited to one-port devices like diodes; feedback oscillator circuits with two-port amplifying devices such as transistors and tubes also have negative resistance. At high frequencies, three terminal devices such as transistors and FETs are also used in negative resistance oscillators. At high frequencies these devices do not need a feedback loop, but with certain loads applied to one port can become unstable at the other port and show negative resistance due to internal feedback. The negative resistance port is connected to a tuned circuit or resonant cavity, causing them to oscillate. High-frequency oscillators in general are designed using negative-resistance techniques.

Some of the many harmonic oscillator circuits are listed below:

Active devices used in oscillators and approximate maximum frequencies

Device	Frequency
Triode vacuum tube	~1 GHz
Bipolar transistor (BJT)	~20 GHz
Heterojunction bipolar transistor (HBT)	~50 GHz
Metal–semiconductor field-effect transistor (MESFET)	~100 GHz
Gunn diode, fundamental mode	~100 GHz
Magnetron tube	~100 GHz
High electron mobility transistor (HEMT)	~200 GHz
Klystron tube	~200 GHz
Gunn diode, harmonic mode	~200 GHz
IMPATT diode	~300 GHz
Gyrotron tube	~600 GHz

• Armstrong oscillator, a.k.a. Meissner oscillator
• Clapp oscillator
• Colpitts oscillator
• Cross-coupled oscillator
• Dynatron oscillator
• Hartley oscillator
• Opto-electronic oscillator
• Pierce oscillator
• Phase-shift oscillator
• Robinson oscillator
• Tri-tet oscillator
• Vackář oscillator
• Wien bridge oscillator

Relaxation oscillator

Main article: Relaxation oscillator

A nonlinear or relaxation oscillator produces a non-sinusoidal output, such as a square, sawtooth or triangle wave. It consists of an energy-storing element (a capacitor or, more rarely, an inductor) and a nonlinear switching device (a latch, Schmitt trigger, or negative-resistance element) connected in a feedback loop. The switching device periodically charges and discharges the energy stored in the storage element thus causing abrupt changes in the output waveform.

Square-wave relaxation oscillators are used to provide the clock signal for sequential logic circuits such as timers and counters, although crystal oscillators are often preferred for their greater stability. Triangle-wave or sawtooth oscillators are used in the timebase circuits that generate the horizontal deflection signals for cathode ray tubes in analogue oscilloscopes and television sets. They are also used in voltage-controlled oscillators (VCOs), inverters and switching power supplies, dual-slope analog to digital converters (ADCs), and in function generators to generate square and triangle waves for testing equipment. In general, relaxation oscillators are used at lower frequencies and have poorer frequency stability than linear oscillators.

Ring oscillators are built of a ring of active delay stages. Generally the ring has an odd number of inverting stages, so that there is no single stable state for the internal ring voltages. Instead, a single transition propagates endlessly around the ring.

Some of the more common relaxation oscillator circuits are listed below:

• Multivibrator
• Pearson–Anson oscillator
• Ring oscillator
• Delay-line oscillator
• Royer oscillator

Voltage-controlled oscillator (VCO)

Main article: Voltage-controlled oscillator

An oscillator can be designed so that the oscillation frequency can be varied over some range by an input voltage or current. These voltage controlled oscillators are widely used in phase-locked loops, in which the oscillator's frequency can be locked to the frequency of another oscillator. These are ubiquitous in modern communications circuits, used in filters, modulators, demodulators, and forming the basis of frequency synthesizer circuits which are used to tune radios and televisions.

Radio frequency VCOs are usually made by adding a varactor diode to the tuned circuit or resonator in an oscillator circuit. Changing the DC voltage across the varactor changes its capacitance, which changes the resonant frequency of the tuned circuit. Voltage controlled relaxation oscillators can be constructed by charging and discharging the energy storage capacitor with a voltage controlled current source. Increasing the input voltage increases the rate of charging the capacitor, decreasing the time between switching events.

History

The first practical oscillators were based on electric arcs, which were used for lighting in the 19th century. The current through an arc light is unstable due to its negative resistance, and often breaks into spontaneous oscillations, causing the arc to make hissing, humming or howling sounds which had been noticed by Humphry Davy in 1821, Benjamin Silliman in 1822, Auguste Arthur de la Rive in 1846, and David Edward Hughes in 1878. Ernst Lecher in 1888 showed that the current through an electric arc could be oscillatory. An oscillator was built by Elihu Thomson in 1892 by placing an LC tuned circuit in parallel with an electric arc and included a magnetic blowout. Independently, in the same year, George Francis FitzGerald realized that if the damping resistance in a resonant circuit could be made zero or negative, the circuit would produce oscillations, and, unsuccessfully, tried to build a negative resistance oscillator with a dynamo, what would now be called a parametric oscillator. The arc oscillator was rediscovered and popularized by William Duddell in 1900. Duddell, a student at London Technical College, was investigating the hissing arc effect. He attached an LC circuit (tuned circuit) to the electrodes of an arc lamp, and the negative resistance of the arc excited oscillation in the tuned circuit. Some of the energy was radiated as sound waves by the arc, producing a musical tone. Duddell demonstrated his oscillator before the London Institute of Electrical Engineers by sequentially connecting different tuned circuits across the arc to play the national anthem "God Save the Queen". Duddell's "singing arc" did not generate frequencies above the audio range. In 1902 Danish physicists Valdemar Poulsen and P. O. Pederson were able to increase the frequency produced into the radio range by operating the arc in a hydrogen atmosphere with a magnetic field, inventing the Poulsen arc radio transmitter, the first continuous wave radio transmitter, which was used through the 1920s.

A 120 MHz oscillator from 1938 using a parallel rod transmission line resonator (Lecher line). Transmission lines are widely used for UHF oscillators.

The vacuum-tube feedback oscillator was invented around 1912, when it was discovered that feedback ("regeneration") in the recently invented audion vacuum tube could produce oscillations. At least six researchers independently made this discovery, although not all of them can be said to have a role in the invention of the oscillator. In the summer of 1912, Edwin Armstrong observed oscillations in audion radio receiver circuits and went on to use positive feedback in his invention of the regenerative receiver. Austrian Alexander Meissner independently discovered positive feedback and invented oscillators in March 1913. Irving Langmuir at General Electric observed feedback in 1913. Fritz Lowenstein may have preceded the others with a crude oscillator in late 1911. In Britain, H. J. Round patented amplifying and oscillating circuits in 1913. In August 1912, Lee De Forest, the inventor of the audion, had also observed oscillations in his amplifiers, but he didn't understand the significance and tried to eliminate it until he read Armstrong's patents in 1914, which he promptly challenged. Armstrong and De Forest fought a protracted legal battle over the rights to the "regenerative" oscillator circuit which has been called "the most complicated patent litigation in the history of radio". De Forest ultimately won before the Supreme Court in 1934 on technical grounds, but most sources regard Armstrong's claim as the stronger one.

The first and most widely used relaxation oscillator circuit, the astable multivibrator, was invented in 1917 by French engineers Henri Abraham and Eugene Bloch. They called their cross-coupled, dual-vacuum-tube circuit a multivibrateur, because the square-wave signal it produced was rich in harmonics, compared to the sinusoidal signal of other vacuum-tube oscillators.

Vacuum-tube feedback oscillators became the basis of radio transmission by 1920. However, the triode vacuum tube oscillator performed poorly above 300 MHz because of interelectrode capacitance. To reach higher frequencies, new "transit time" (velocity modulation) vacuum tubes were developed, in which electrons traveled in "bunches" through the tube. The first of these was the Barkhausen–Kurz oscillator (1920), the first tube to produce power in the UHF range. The most important and widely used were the klystron (R. and S. Varian, 1937) and the cavity magnetron (J. Randall and H. Boot, 1940).

Mathematical conditions for feedback oscillations, now called the Barkhausen criterion, were derived by Heinrich Georg Barkhausen in 1921. The first analysis of a nonlinear electronic oscillator model, the Van der Pol oscillator, was done by Balthasar van der Pol in 1927. He showed that the stability of the oscillations (limit cycles) in actual oscillators was due to the nonlinearity of the amplifying device. He originated the term "relaxation oscillation" and was first to distinguish between linear and relaxation oscillators. Further advances in mathematical analysis of oscillation were made by Hendrik Wade Bode and Harry Nyquist in the 1930s. In 1969 K. Kurokawa derived necessary and sufficient conditions for oscillation in negative-resistance circuits, which form the basis of modern microwave oscillator design.

Public sector ethics

From Wikipedia, the free encyclopedia

Ethics in the public sector is a broad topic that is usually considered a branch of political ethics. In the public sector, ethics addresses the fundamental premise of a public administrator's duty as a "steward" to the public. In other words, it is the moral justification and consideration for decisions and actions made during the completion of daily duties when working to provide the general services of government and nonprofit organizations. Ethics is defined as, among others, the entirety of rules of proper moral conduct corresponding to the ideology of a particular society or organization (Eduard). Public sector ethics is a broad topic because values and morals vary between cultures. Despite the differences in ethical values, there is a growing common ground of what is considered good conduct and correct conduct with ethics. Ethics are an accountability standard by which the public will scrutinize the work being conducted by the members of these organizations. The question of ethics emerges in the public sector on account of its subordinate character.

Decisions are based upon ethical principles, which are the perception of what the general public would view as correct. Ensuring the ethical behavior in the public sector requires a permanent reflection on the decisions taken and their impact from a moral point of view on citizens. Having such a distinction ensures that public administrators are not acting on an internal set of ethical principles without first questioning whether those principles would hold to public scrutiny. It also has placed an additional burden upon public administrators regarding the conduct of their personal lives. Public sector ethics is an attempt to create a more open atmosphere within governmental operations.

Government ethics

Government ethics constitutes the application of ethical rules to government. It is that part of practical jurisprudence, or the philosophy of law, that governs the operation of government and its relationship with the people that it governs. It covers issues of honesty and transparency in government, dealing with matters such as bribery, political corruption, police corruption, legislative ethics, regulatory ethics, conflict of interest, avoiding the appearance of impropriety, open government, and legal ethics.

The US office of government ethics was initiated by the Ethics in Government Act of 1978 to provide overall leadership and policy direction for an ethics program in the Executive branch of government. This same picture is mirrored, albeit in a patchy way, across US state administrations. Altogether the US model of Public sector ethics has become highly regulated and, some would say, cumbersome.

Government officials serve the people, managing the resources of others. Along with this stewardship, there is an expectation from the public that in conducting daily activities, the officials will practice fairness and equality. They are also expected to maintain openness in their workings to ensure that they are operating within the public's perception of what is "right." This concept of ethics, a branch of philosophy which seeks to address morality, is not a relatively new idea within government. Niccolò Machiavelli wrote The Prince, which serves as a manual to illustrate what a monarchy should do to maintain power. This treatise is often viewed as a tool of how a public official should not act in modern society, as it is an enumeration of the specific steps one should take to maintain control and power. This idea of control and power conflicts with the underlying principle of being a steward to the general public. As such, this treatise is a springboard for ethical issues in modern-day times.

Paul Douglas, a former United States Senator from Illinois, argues that while many may secretly follow Machiavelli in their heart, most do not. “Instead, most men want a life of integrity and goodwill in which public officials are stewards rather than masters and treat their jobs as a means of helping people rather than dominating them”.

Douglas further argues why ethical practices are needed. “Our government is now so huge and affects our lives so directly that we cannot be content with merely a moderately decent level of behavior on the part of our public officials. For even a small percentage of misbehavior on the part of these officials can do a vast amount of harm”.

Regulatory ethics is a body of law and practical political philosophy that governs the conduct of civil servants and the members of regulatory agencies. It addresses issues such as bribery and the relationship of civil servants with the businesses in the industries they regulate, as well as concerns about transparency, freedom of information and sunshine laws, and conflict of interest rules.

While Machiavelli and Douglas are distant in time, the two opposing viewpoints of the types of public administrators, and the ethical stance of the decisions they make, are very relevant today. Further illustrating the bifurcation of thought on ethics in government, Cody and Lynn discuss the two opposing factors: utilitarian's and deontologists.

Utilitarians: Believe that the end sought justifies the means to that end. In other words, if an ethical solution is more costly, a utilitarian will argue from a standpoint of efficiency or effectiveness to justify a less ethical solution.

Deontologists: Believe that certain absolute principles should be obeyed, regardless of the consequences. An example of an absolute principle would be honesty.

The definition of these two behavioral models is not necessarily exclusive. It is possible for a person to make a decision based upon a utilitarian stance and then follow a deontological stance for a separate decision. This is because the concept of ethics is vague and ultimately is based upon principles and values, which will differ among situations and people.

Public Sector Ethics vs. Government Ethics

Public sector ethics deals with ethics for those who serve in the public sector- primarily governmental and elected officials focusing on the public, whom they serve. While public sector ethics overlaps in part with government ethics, it can be considered a separate branch in that government ethics is only focused on moral issues relating to governments, including bribery and corruption, whilst public sector ethics also encompasses any position included in the public administration field. Public administration ethics does cover relations among politicians, but it also covers politicians and the concerned parties in the outside world: elected public servants, the media, public sector entities, and individuals.

Ethical standards

John Rohr, in defining bureaucrats as public administrators, approaches ethic standards in government as a requirement due to the nature of the work of administrators. He writes, “because bureaucrats govern through authority that is discretionary, and because they are not elected, the ordinary means of popular control are inapplicable”. Rohr assumes that public administrators are working to benefit the general public's needs. When an elected official does not act in line with the public's expectations, they can be removed from office. However, public administrators are protected with due process rights as government employees, and ethical violations can be difficult to justify the removal of a person from an office.

Many questions about how ethics should be addressed in government exist. According to Cody and Lynn, the debate centers on the extent to which one would like to detail ethical standards. For example, they cite the general litmus test for administrators regarding whether or not they would like to hear about their actions on the front page of tomorrow's newspaper. That is, public officials should gauge their decisions through the lens of the public reading about the decision on the front page of a newspaper. If it would be viewed as a problem by the public, then the administrator should refrain from the action in question.

The Honest Person Rule: Unless there is an underlying honesty within people, a set of ethical rules is meaningless. This supporting argument for the general guidelines maintains that for ethical standards to be practical an individual must be ethically sound from the beginning. As Cody and Lynn point out, it is possible for a public official to act unethically, but not be personally dishonest.

The litmus test example and the Honest Person Rule are broad standards without much definition. As a consequence, broadly defined ethical standards are difficult to assess regarding concerns of ethical violations. In order to have greater accountability, more specific standards are needed, or a statement of applied ethics.

To further provide some definition, Rohr classifies ethics in government with some of the approaches that have been taken. The USDA devised a system where employees were asked questions and then asked to rank the actions as permissible, not permissible, and permissible with prior written approval. Rohr argues that this type of approach, known as the Low Road merely places an understanding of what not to do in order to steer clear of trouble (1978, pp. 53–54). This approach does not assist an employee in providing a standard for what is truly ethical behavior.

The High Road, according to Rohr, is the basis of decisions upon a pursuit for social equity, which is based upon political philosophy and humanistic psychology.

Rohr finds problems with both the Low Road and High Road approaches and bases his argument on regime values, or “the values of that political entity that was brought into being by the ratification of the Constitution that created the present American republic” (1978, p. 59). He contends that regime values are built upon three considerations:

1. Ethical norms should be derived from the salient values of the regime;
2. These values are normative for bureaucrats because they have taken an oath to uphold the regime; and
3. These values can be discovered in the public law of the regime.

The basic contention upon which Rohr builds his argument is that rulings by the Supreme Court are sufficient measures upon which an ethical framework can be constructed. Rohr argues that this framework for ethical standards is strong because it relies upon a system of checks and balances in the judicial system and because it is built upon the interpretation of framers' intents of how and why government exists.

Levels of ethical decision-making

Terry Cooper is an often-cited author in the field of public administration ethics. His book, The Responsible Administrator, is an in-depth attempt to bridge the philosophical points of ethics and the complex workings of public administration. While not revolutionary, his work has become a focal point around which ethical decision-making in the public sector are made. In The Responsible Administrator, he states that public administrators make decisions daily according to a distinctive four-level process. The four levels are:

The Expressive Level: At this stage, a person responds to a situation with "spontaneous, reflective expressions of emotion ... which neither invite a reply nor attempt to persuade others".

The Level of Moral Rules: This is the first level at which we begin to question actions and begin to look for alternatives and consequences. The responses at this level are often built upon "moral rules we acquire through the socialization process from our families, religious affiliations, education and personal experiences." Decisions on how to handle the situation are then whittled down based on what we feel is the most appropriate action within our own personal moral bank.

The Level of Ethical Analysis: There are times when a personal moral code will seem inadequate for the situation, or that the alternatives and consequences do not feel right. When this occurs, a person has entered this level and begins to examine their ethical principles, or "statements concerning the conduct or state of being that is required for the fulfillment of a value; it explicitly links a value with a general mode of action". Particularly, at this level, one begins to reexamine their personal values, and may eventually disagree with actions to such an extent that they will become "whistleblowers."

The Post-ethical Level: At this level, questions arise about one's view of the world and human nature, how we know anything to be true, and the meaning of life. Here there is a philosophical examination as to why ethical standards are important and relevant to the individual.

These levels are progressive and as an individual begins to move from level to the next, they will begin to question increasingly more the fundamental assumptions upon which the decision-making process is built. It is important to understand the level of thinking upon which a decision is made to ensure that a decision has been tested for strength and a public sense of validity.

Cooper's decision-making model

Cooper devised a method of moving from an ethical problem to appropriate alternatives and consequences. This model follows a sequential, rational approach to ethical decision-making. This method utilizes description and prescription, where public administrators begin to describe to themselves and others an objective state of affairs, and then begin to suggest steps to change the situation.

The steps to this process are as follows:

1. The Descriptive Task: A problem is often presented in a fragmented, distorted fashion coupled with judgmental language and inflections. Cooper contends that the administrator is in a position to have more complete knowledge when an issue is brought forward. Additionally, an administrator should attempt to describe questionable situations void of personal feelings (moving beyond the expressive level).
2. Defining the Ethical Issue: Often the most misinterpreted step, with defining the ethical issue, an administrator is not charged with defining the problem. Instead, there is an examination of what is the underlying ethical value that is being addressed. Often, there is a decision made because of a problem, without examination of the ethical issue. This is damaging to the process of decision-making because it harms one's ethical analysis skills and ethical identity. This is true because situations can differ, and practical decision-making may lead to inconsistencies without an ethical base (1990, p. 20).
3. Identifying Alternative Courses of Action: Using a rationalistic approach, an administrator, with as complete knowledge of the situation as possible and an assessment of the ethical issue at hand, identifies all the plausible courses of action in response to the situation.
4. Projecting the Possible Consequences: In this stage, all positive and negative results of each alternative are examined. When discovering the possible positive and negative outcomes of an action, administrators use their moral imagination, or the imagined enactment of how alternatives will play out. Ideally, as more consequences are enumerated, the ethical decision-making process will be strengthened.
5. Finding a Fit: The appropriate solution or alternative is a balance of four elements:
   1. Moral Rules: Those basic standards that can be attributed to the alternatives and their consequences.
   2. Rehearsal of Defenses: The assessment and alignment of alternatives with the accepted norms of the wider professional organization and political communities of which we are a part.
   3. Ethical Principles: In assessing the moral rules, it may become clear that certain moral values are competitive. Therefore, it becomes difficult to say that an alternative which support social justice is more correct than the security of an individual or the organization. Here, an administrator assesses alternatives and their moral values under the light of the level of ethical analysis - deciding how the hierarchy of moral rules is structured and ultimately influencing the final decision.
   4. Anticipatory Self-Appraisal: Simply put, this analysis of alternatives requires an internal reflection of whether an administrator feels that an alternative fits within what he or she perceives to be their own personality. This is an examination of whether an alternative will meet our need to feel satisfied with the decision.

By following Cooper's model of ethical decision-making, a public administrator is able to create a more concrete process by which to assess individual steps that were taken in reaching a decision. This ensures that at each point, an effort was made by the administrator to uphold ethical principles and that fairness and equality were the standard. An administrator's decision must be able to withstand scrutiny to ensure that there is a continued trust and respect for accountability among employees and the public in the administrator's ability to conduct his/her duties.

Politics and ethics

Public administrators act independently of legislators and most elected officials. This ensures that those on elections boards can operate independently of political influence. This is also true of law enforcement. Unfortunately, enforcing ethical violations can lead to consequences for the public administrator. While an officer can enforce a law against an elected official, the elected official can place pressure on others to force the officer to work a night shift or decrease the department.

Rohr would argue that politics and administration are not separate, but are present at the same time when a public administrator makes decisions. He states that the problem with public administrators “is not that bureaucrats are excessively involved in policy formulation but that they are involved at all. This is a problem for a democratic society because to influence public policy as a public official is to govern”. In other words, those officials who are influencing decisions are taking on the role of those elected by the public without a responsibility of having to answer to the public for decisions made.

However, because there can be large political obstacles, it can be difficult for an administrator to overcome ethical concerns within an organization. Sometimes, the culture of an organization is unethical, at which time, it would be useless to bring up ethical concerns within the organization. In the public sector and nonprofits, when this is the case, individuals will often attempt to bring outside scrutiny on to the organization. This is typically done by leaking the ethical concerns to the general media. Such an act is known as whistleblowing.

Whistleblowing: After using all available means for working within the system, an employee of a governmental agency reports a problem to other governmental agencies or to the general public directly. The problem for whistleblowing on all levels of government (federal, state, and local) is that there are very few protections for these individuals.

Ethics and the personal life of administrators

There are several factors of a person's private life that are often viewed as something that is not made available to the public. When a person enters into a public life, often, aspects of their private life are made public.

Health: It is important, in the public's eye, that a public official be physically sound when conducting the duties of their office. For example, when Ronald Reagan had an assassination attempt, he was often reporting how healthy he was. This may have been an attempt to prevent the transfer of power to his Vice President. However, because of the mandate of a transfer of power, it was necessary for the public to understand his overall condition.

Finances: A public official may be a strong steward of public funds, but may have personal financial issues (i.e. failure to pay taxes, etc.). Disclosure of finances is particularly important, ethically, for the public to decide an official's ability to properly manage public funds and to assess an individual's potential for giving into politically charged financial pressure. Opposing viewpoints to this argue that public officials should not have to disclose financial information because they are sometimes linked to personal contacts that prefer to remain anonymous.

Sexual Misconduct: The common view is that a public official's sexual life is subject to scrutiny. This is due to the assumption that any sexual misconduct may lead to the manipulation of the official's daily decisions. It is thereby often the subject of attention when sexual misconduct becomes known to the public.

Appearance of Impropriety: Officials should make public any possible conflicts of interest prior to their actions, in order to avoid public scrutiny when making decisions that could be construed in favor of a personal interest.

Ethical Climate in the Public Sector

Ethical climate in the public sector refers to the psychological conditions present in the public sector workplace and how those conditions influence a public sector employees ethical decision making. One way of interpreting public sector ethics from a theoretical perspective is to view a workers behavior as a function of their psychological field. It is theorized that understanding the ethical climate in which one works explains ones decisions making and can differentiate between and explain why one would make ethical or unethical choices. A study was done examining the ethical climate in the sector through analyzing surveys in which public sector employees responded to a variety of different scenarios where ethical decision making came into play. The researchers looked for correlations between ethical climate environments and the responses to this survey and found that certain ethical climates were linked to positive ethical decision making and some were linked to worse ethical decision making, supporting the researchers thesis.