
1. Application of C.P
1.1. Numerical analysis
1.1.1. a branch of mathematics to solve diff problems for which on exact solu. does not exist approximately ( numerically ) -> it transforms the analysis of problem form complicated math into in to simple arithmetic
1.1.2. why computer for N.A 1- faster 2- more efficient( error - free) 3- bigger storge volume 4- manipuation of stored in formtion
1.1.3. Example 1- diff .equation 2- function evaluation 3- integration 4- find roots of equa
1.1.4. posstive and nigative of N.A
1.1.4.1. positive it make some prograse in untauched problem end as simpler arimathmetics
1.1.4.2. negative the solu is not the fiind solu ( just on approxemation ) some feature is lost i n the solu the need large # of iteration and large storge
1.2. slimulations
1.2.1. to use computers to do vertial exp to study the behavior of a system by studing a simpler syst
1.2.1.1. math model transforating the physics to task to be excuted by PC
1.2.1.2. EXP lab sample -> setup -> calibrations -> messurmints -> data virtual exp math model -> program -> testing -> computation -> data
1.2.1.3. nigative * give the most simpliify form * no skills positve * less effort * possibity to difficult EXP , unsafe , expisive
1.2.1.4. EX simulating mechanics simulating molecules weather forcast virtual realty explosiv
1.3. visualization
1.3.1. to produce graphic ( grphs / picture animated ) to desctibe the mathmatical model of system --> translating the model into a image to give a conception of the mathematical abstract eyes can recongnizeth the trend and behavior pattern that mind can miss
1.4. symbolic algebra S.A
1.4.1. symbolic & algebraic computations ( SAC) software used to preform S.A on computer for algebric systems to use computers to preform algebric operations & to use then to find exact solu
1.5. collecting and analysis of Data
1.5.1. * collection of data = data acquisition * controlling of data * analysis ( processing & manipulation ) of data * of line experment ( collection of signals mesurment with the world condition into digital numeric values )
2. why to use Comp. physics
2.1. 1 there is few # of phys problem that can solved exactly 2 many aspect of routine work in physics can be computerized 3 it can inteduce new ways fo represent phys system 4 completedly safe on less expensive
3. computer aidid problem solving
3.1. basic techniqes to solve problem by the aid of computers
3.1.1. scientific computing system
3.1.1.1. software devobed to scientific work ( with more emphasis on science less on programing )
3.1.1.2. EX mathimatica of walfrom mathlab of math work mathCAD of math and eng mople of mople soft igor of wave matrics
3.1.1.3. usefull S.C.S has the following feature * built-in programing * ready made scientific pakages * a bility to be linked with other software or lab instrument * publishing / featues / capablities
3.1.2. programming language
3.1.2.1. formal laguage that comprasing a set of rules / opration / calculations to perform the job
3.1.2.2. EX c,c#,c++ pascal python fortran
3.1.2.3. _ good pro P.L has the following featur * easy to read * robust / strong language {error reporting } * easy to use * self_documented
3.2. step to follow to use computer in real problem solving 1- undrestand the physics & math of your problem 2- identify the part of the problem that need to a computer 3- write the algorithem 4- translate the algorithem into computer code ( thats can be undrestood by computer ) 5- running the program code & debugging 6- run the progrem
3.2.1. Algorithm abstraction of a computer code
3.2.1.1. a set of instrucation, rule , processes in sequence good algroithm - modifiable - efficient ( lless wasted time ) - accurate - error reporting why to start with on algorithm - good easier start of thr program - easier to dibug - easier to modfiy - give more insight about what you are doing
3.2.1.2. how to write a build in algorithm
3.2.1.2.1. pesudo code ( textual )
3.2.1.2.2. both
3.2.1.2.3. flow chart (graphical)
3.3. Types of comp-related error
3.3.1. 1- Truncation Error * cutting off part of a func[formala , equ, series] * due to mathematical simplfication 2- Round off error *cut off part of a numper # * computer are integer machines with 2 way to represent no.s * fixed point represtation(1,2,3) * floting point(3.14) 3- Error in the orginal data - the math model abtaned by the PC is poorly represents the problem very common in simulations 4- Blunders - human error ( sysntax error ) 5- propgated Error ( due the error in the preceding step)