Computational physics is the study and implementation of numerical analysis to solve problems in physics for which a quantitative theory exists. Computational physics was the first application of modern computers in science, is now a subset of computational science, it is sometimes regarded as a subdiscipline of theoretical physics, but others consider it an intermediate branch between theoretical and experimental physics, a third way that supplements theory and experiment. In physics, different theories based on mathematical models provide precise predictions on how systems behave, it is the case that solving the mathematical model for a particular system in order to produce a useful prediction is not feasible. This can occur, for instance, when the solution does not have a closed-form expression, or is too complicated. In such cases, numerical approximations are required. Computational physics is the subject that deals with these numerical approximations: the approximation of the solution is written as a finite number of simple mathematical operations, a computer is used to perform these operations and compute an approximated solution and respective error.

There is a debate about the status of computation within the scientific method. Sometimes it is regarded as more akin to theoretical physics. While computers can be used in experiments for the measurement and recording of data, this does not constitute a computational approach. Computational physics problems are in general difficult to solve exactly; this is due to several reasons: lack of algebraic and/or analytic solubility and chaos. For example, - apparently simple problems, such as calculating the wavefunction of an electron orbiting an atom in a strong electric field, may require great effort to formulate a practical algorithm. On the more advanced side, mathematical perturbation theory is sometimes used. In addition, the computational cost and computational complexity for many-body problems tend to grow quickly. A macroscopic system has a size of the order of 10 23 constituent particles, so it is somewhat of a problem. Solving quantum mechanical problems is of exponential order in the size of the system and for classical N-body it is of order N-squared.

Many physical systems are inherently nonlinear at best, at worst chaotic: this means it can be difficult to ensure any numerical errors do not grow to the point of rendering the'solution' useless. Because computational physics uses a broad class of problems, it is divided amongst the different mathematical problems it numerically solves, or the methods it applies. Between them, one can consider: root finding system of linear equations ordinary differential equations integration partial differential equations matrix eigenvalue problem All these methods are used to calculate physical properties of the modeled systems. Computational physics borrows a number of ideas from computational chemistry - for example, the density functional theory used by computational solid state physicists to calculate properties of solids is the same as that used by chemists to calculate the properties of molecules. Furthermore, computational physics encompasses the tuning of the software/hardware structure to solve the problems.

It is possible to find a corresponding computational branch for every major field in physics, for example computational mechanics and computational electrodynamics. Computational mechanics consists of computational fluid dynamics, computational solid mechanics and computational contact mechanics. One subfield at the confluence between CFD and electromagnetic modelling is computational magnetohydrodynamics; the quantum many-body problem leads to the large and growing field of computational chemistry. Computational solid state physics is a important division of computational physics dealing directly with material science. A field related to computational condensed matter is computational statistical mechanics, which deals with the simulation of models and theories that are difficult to solve otherwise. Computational statistical physics makes heavy use of Monte Carlo-like methods. More broadly, it concerns itself with in the social sciences, network theory, mathematical models for the propagation of disease and the spread of forest fires.

On the more esoteric side, numerical relativity is a new field interested in finding numerical solutions to the field equations of general relativity, computational particle physics deals with problems motivated by particle physics. Computational astrophysics is the applic

Maximilian Friedrich Julius Consbruch was a German West Prussian classical philologist and gymnasium principal, known for his studies of Greek lyric and the work of Hephaestion. Consbruch was the son of a German-speaking Prussian parson and born in Elbing, West Prussia, Kingdom of Prussia, he studied classical philology and theology at the Day Gymnasium in Elbing until 1884 in Berlin until 1885 in Breslau. He spent time assigned to the Berlin-Brandenburg Academy of Sciences and Humanities, working on Greek etymology and spending some months in Italy. Afterwards he lived in Halle and taught there from 1892-1894 at the Latin High School of the Francke Foundation from 1894-1909 at the local City Gymnasium, from 1902-1909 he was an assistant lecturer in philology at the University of Halle. From 1909-1911 he was director of the Carl-Frederick-Gymnasium Eisenach, now the Martin-Luther-Gymnasium Eisenach. From 1911-1914 he was director of the Gymnasium of Saint Mary Magdalene Gymnasium Breslau, a German-language school, now a Polish lyceum.

His subsequent positions were as a teacher operating in the area of ancient philological research and as a writer of articles for Pauly's Realencyclopädie der Classischen Altertumswissenschaft. De Hephaestioneis qui circumferuntur peri poiēmatos commentariis, Breslau 1889 De veterum peri poiēmatos doctrina: acc. commentarii qui circumferuntur peri poiēmatos, Breslau 1890 Hephaestionis enchiridion, Leipzig 1906 Deutsche Lyrik des 19. Jahrhunderts, Leipzig 1909

The Sport Racer is an American homebuilt racing aircraft, designed and produced by Sport Racer Inc of Valley Center, Kansas. When it was available the aircraft was supplied in the form of plans for amateur construction; the Sport Racer features a cantilever mid-wing, a two-seats-in-tandem enclosed cockpit under a bubble canopy, fixed conventional landing gear with wheel pants and a single engine in tractor configuration. The aircraft fuselage is made from welded 4130 steel tubing; the 22.00 ft span wing has a wooden structure, covered in doped aircraft fabric and has a wing area of 81.00 sq ft. The standard engine used is a 230 hp Ford Motor Company V-6 automotive conversion powerplant; the Sport Racer has a typical empty weight of 1,175 lb and a gross weight of 1,850 lb, giving a useful load of 675 lb. With full fuel of 30 U. S. gallons the payload for the pilot and baggage is 495 lb. The standard day, sea level, no wind, take off with a 230 hp engine is 1,500 ft and the landing roll is 1,600 ft.

The manufacturer estimated the construction time from the supplied plans as 1600 hours. Data from AeroCrafterGeneral characteristics Crew: one Capacity: one passenger Length: 21.15 ft Wingspan: 22.00 ft Wing area: 81.00 sq ft Empty weight: 1,175 lb Gross weight: 1,850 lb Fuel capacity: 30 U. S. gallons Powerplant: 1 × Ford Motor Company V-6, six cylinder, liquid-cooled, four stroke automotive conversion engine, 230 hp Propellers: 2-bladed fixed pitchPerformance Maximum speed: 225 mph Cruise speed: 175 mph Stall speed: 62 mph Range: 525 mi Service ceiling: 18,000 ft Rate of climb: 900 ft/min Wing loading: 22.8 lb/sq ft List of aerobatic aircraft List of seaplanes and amphibious aircraft Photo of a Sport Racer