An Unique SPICE Model of Photodiode with Slowly Changeable Carriers Velocities

Size: px
Start display at page:

Download "An Unique SPICE Model of Photodiode with Slowly Changeable Carriers Velocities"

Transcription

1 J Infrare Milli Terahz Waves DOI.7/s An Unique SPICE Moel of Photoioe with Slowly Changeable Carriers Velocities Petar S. Matavulj & Miomira V. Lazović & Jovan B. Raunović Receive: 6 February 27 / Accepte: 2 November 2 # Springer Science+Business Meia, LLC 2 Abstract This paper eals with a relatively new SPICE moel of a P-i-N photoioe. The moel inclues a change of velocities of electrons an holes, ue to the voltage rop on the eges of the photoioe, which epens on the time form of input excitation. We have erive the moel of the P-i-N photoioe for igital input excitation i.e. for Heavisie s square wave time excitation. The moel is incorporate in SPICE program an simulate with it. The moel an the limitations of the moel itself are observe. The output results are compare with the similar ones. It is suggeste when it is practical to use the moel, an etermine the photoioe working omain regime when the moel gives accurate results. Keywors Equivalent circuits. P-i-N photoioe. Program SPICE. Quasi-linear working regime. Transient response Introuction In the last ecae there were a few significant trials to create the equivalent electrical moel of photoioe [ 5], as well as it is alreay one for a number of lasers [6 8]. The purpose of these observations is to establish universal electrical moel for the escription of the whole optical integrate circuit, an to introuce one program for solving the input-output epenences of all parts of the circuit. The aim is to give the moel with, as much as possible, relevant physical processes inclue in it, an to solve it using a simple an cheap program. All mentione resulte with the iea that it woul be very convenient to simulate a photoioe using an electrical moel, an solving it response with SPICE program. The previous works on this subject [ 5], eal with photoioes in linear working regime, where not a single effect of nonlinearity was observe, because of ifficulties in P. S. Matavulj (*) : J. B. Raunović Faculty of Electrical Engineering, University of Belgrae, Bulevar kralja Aleksanra 73, 2 Belgrae, Serbia matavulj@etf.rs M. V. Lazović Serbian Energy Efficiency Agency, Omlainskih brigaa, 7 Belgrae, Serbia

2 J Infrare Milli Terahz Waves escription of multiimensional transport equations with just one time imension use in electric circuits. But, nonlinearity in response becomes important fact when we eal with relatively high igital pulses in high-spee optical communications. In the paper we consiere an simulate a bounary situation, when the voltage rop on photoioe is enough high to generate nonlinearity in response, but is still not enough to generate space charge effect. The paper suggests possibly one new approach, in calculating photoioe response, which takes into account the effect of the change of carriers velocities. Velocities are changeable in the moel an that is the main ifference comparing to papers [ 5] which use constant saturation velocities. The moel gives more precise results in the working regimes wherein the carriers velocities epen a lot on the photoioe voltage i.e. wherein the electric fiel ecreases below kv/cm ue to the high input photon flux. Also, the moel is completely applicable for the linear regimes with the constant carriers velocities. The nonlinearity effect observe here happens only ue to the influence of photoioe voltage on carriers velocities [9 2]. The effect becomes relevant when the photoioe is not highly saturate, so the carriers velocities are not simple saturation velocities, an when the energy of light pulses varies (so the average carriers velocities alter from pulse to pulse). From one sie we propose physical moel how to calculate mean values for carriers concentrations an currents in the case of weak nonlinearity, an from other sie we propose how to implement it in SPICE. We think that it is almost impossible to solve the continuity equation irectly using SPICE because the program works with one inepenent variable time. So we partially solve continuity equation, an in an equivalent electrical circuit of a P-i-N photoioe we calculate the necessary concentrations of electrons an holes in the subcircuits. The moel is mainly evelope for Heavisie s square wave time input excitation, where first we solve analytically concentrations epenences on the applie voltage time form. We solve the continuity equations treating the velocities as almost as constant, but in calculating the currents we treat them as changeable. This is the correct step as long as the nonlinearity of the regime is not too high i.e. the velocities are almost constant comparing to the change of concentrations in continuity equations. The equivalent electrical moel, of the P-i-N photoioe, is incorporate into SPICE an results are compare with the similar results which o not take into account the changes of carriers velocities. Also, in FORTRAN is evelope a moel wherein the overpasse path is calculate by integral of voltage, with the aim of comparing the results with less accurate SPICE results. The last proceure enable us to efine the range of relevant working regime of the P-i-N photoioe, where our SPICE moel is fully applicable. 2 Equivalent moel We consiere P-i-N photoioe stanar electric circuit presente in Fig.. Several assumptions are mae: ) the with of the P region is much smaller than the with of the i region so there is no relevant generation of carriers in P region an the main current is rift current in i region; 2) the iffusion current in the N region is taken into account an in P is neglecte accoring to assumption ; 3) there is no space charge effect we consier the situation when the input signal is high but not that orer of magnitue to create space charge effect; 4) the ark current is neglecte because it is a few egrees of magnitue lower than the photocurrent; an 5) nonlinearity exists only as the consequence of the voltage rop on the loa resistance, []. These assumptions are use to simplify moel an

3 J Infrare Milli Terahz Waves -Vcc U(t) I(t) P I N light R I(t) Fig. The electric circuit with the P-i-N photoioe. they are vali if we eal with low, meium an high, but not overmuch high, incient light signal as in the case analyze in [, 2]. In establishing of the photoioe s equivalent electric circuit, which is going to be inserte into program SPICE, we start from the equation of the main electric circuit from Fig. : UðtÞ ¼V CC RIðtÞ: The above expression escribes the change of the photoioe voltage ue to the flow of the photocurrent. In the above equation V CC is bias voltage, R is loa resistance an I(t) is the total current flow. In orer to obtain the total current flow I(t) we shoul fin the carriers concentrations an carriers velocities, which play the role in rift currents, an iffusion current. The require concentrations for the case of Heavisie s time input excitation can be obtaine from the results for Dirac s time input excitation. For the case of Dirac s input time excitation mean values, in space, for electrons an holes concentrations are alreay obtaine in [2], given by: hni ¼ expð aþexp@ a Z t t m n ð UðtÞ V ðþ ÞtAA; ð2aþ hpi ¼ exp@ a Z t t m p ð UðtÞ V ÞtA expð aþa: ð2bþ I represents, here, the intensity of incient Dirac s excitation, μ n an μ p stan for electrons an holes mobilities respectively, α is the absorption coefficient, is the with of i region, t represents the time moment when Dirac s impulse appears, U(t) is the photoioe

4 J Infrare Milli Terahz Waves voltage, V is punch-through voltage, an integral of U(t)-V in the exponent stans for the total path which electrons (or holes) pass over the photoioe. In the above expressions miss the Heavesie s members for borer conitions, wherein the total path of the carriers must be less than with of the photoioe. In the case of constant velocities, or slowly changeable velocities, we can use (2a) an (2b) in a ifferent manner as: hi¼ n I ð exp a ð Þexp ð au nðtþðt t ÞÞÞ; ð3aþ Utilizing the property of Dirac s function: hpi ¼ I exp au pðtþðt t Þ expð aþ : ð3bþ ΦðtÞ ¼ Z Φðt Þðt t Þt ; ð4þ where Φ(t) is an arbitrary function in time, an uner the assumption that the velocities are slowly changeable, we can obtain the mean values of carriers concentrations as: hn Φ i ¼ I Z Φðt t Þhn D ðþ t it; ð5aþ hp Φ i ¼ I Z Φðt t Þhp D ðþ t it: ð5bþ where variable t stans for expression (t-t ). In (5a) an(5b) inexes n Φ an p Φ stan for the mean values of concentrations of electrons an holes, for the case of arbitrary function of time input excitation, an <n D > an <p D > are alreay obtaine the mean values of carriers concentrations for Dirac s input excitation, given in (3a) an(3b). The Eqs. 5a an 5b coul be solve analytically in many cases, i.e. for a large number of ifferent incient excitations functions Φ(t). If we replace the arbitrary function with Heavisie s function we can obtain the mean values of concentrations of electrons an holes in i region for Heavisie s input excitation as: hn h i ¼ Φ Zun ðht ð t t ÞÞð expð aþexpðau n tþþt; ð6aþ hp h i ¼ Φ Zup ðht ð t t ÞÞ exp au p t expð aþ t: ð6bþ In the above equations t is the time moments when the Heavisie s starts, an Φ stans for an intensity of Heavesie s function (in physical sense it is the input flux). Here the carriers

5 J Infrare Milli Terahz Waves velocities are marke with υ n an υ p, regarless of whether we work with constant or slowly changeable velocities. Solutions of the Eq. 6a are: For t >t hn h ðtþi ¼ : ð7aþ For t-t </(v n (t)) int hn h ðtþi ¼ t t au n ðtþ ð exp ð a þ au nðtþðt t ÞÞ expð aþþ : ð7bþ An for t-t >/(v n (t)) hn h ðtþi ¼ int u n ðtþ au n ðtþ ð exp a : ð7cþ Here n h marks the mean value (in space) for electrons concentration for the case of Heavisie s input function in time. Also we obtain the mean value for concentration of holes as: For t >t For t-t </(v p (t)) hp h ðtþi ¼ For t-t >/(v p (t)) int hp h ðtþi ¼ hp h ðtþi ¼ : ð8aþ au p ðtþ exp au pðtþðt t Þ expð aþ ð t t Þ : ð8bþ int exp a au p ðtþ ð ð Þ Þ exp ð a Þ : ð8cþ u p ðtþ Int stans for the intensity of Heavisie s function. All above equations are vali in the case of constant or slowly changeable velocities. For the case of Heavisie s square wave input excitation, with intensity int, given with the formula: ht; ð t ; t 2 Þ ¼ int ðht ð t Þ ht ð t 2 ÞÞ; ð9þ it is easy to obtain the carriers concentrations as: hn h ðtþi ¼ hn h ðt; t Þi hn h ðt; t 2 Þi; ðaþ hp h ðtþi ¼ hp h ðt; t Þi hp h ðt; t 2 Þi: ðbþ In this case we first obtain the carriers concentrations for the first Heavisie s signal an then for the secon signal. The rule of superposition can be use as long as the working regime is quasi-linear.

6 J Infrare Milli Terahz Waves In orer to obtain total rift current in i region, besies alreay given expressions for the carriers concentrations, we nee the equations for the carriers velocities. The electron s velocity is given in [9] Eq. 4, here presente with (a), an for the holes velocity we use (b): UðtÞ V u n ¼ m n r ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ; ðaþ ð þ UðtÞ V Þ E 2u ðð UðtÞ V Þ E Þ E c UðtÞ V u p ¼ m p : ðbþ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi E an E c are constants (E ¼ 2 E M þ EM 2 4E2 C, E C ¼ v sat m, E M is constant, v sat is n electron saturation velocity); u represents function which obtains value (for U(t)-V>E ) or (otherwise) epening on the value of expression in brackets; U(t) is the instantaneously photoioe voltage; V is the punchtrough voltage an is the with of i region. The total current flow, as it is alreay mentione, is the sum of total rift current in i region an iffusion current in N region. Using the continuity equation for N region, with borer conitions, we obtain the expression for iffusion current in the case of Heavisie s input excitation as: I pif ¼ int qsd p a 2 exp a g ð Þ ð exp ð g ð t t ÞÞÞ; ð2þ (see in Appenix) where: g ¼ L 2 p a 2 =tp. Here t p is the hole s life time in N region, L p is the hole s iffusion length, S is the photoioe cross section area, D p is hole s iffusion constant, an q is the electron s charge. In the total current flow there is one more term that represents isplacement current the last member in (3): IðtÞ ¼I n þ I p þ I pif þ "S UðtÞ : ð3þ t In the equation I n an I p are rift electrons an holes currents, an ε is ielectric constant. For the series of Heavisie s square waves given by expression: h ¼ int ðht ð t Þ ht ð t 2 ÞÞþint 2ðht ð t 3 Þ ht ð t 4 ÞÞþ...; ð4þ total electrons an hole s concentrations are: hi¼ n hnt; ð t Þi hnt; ð t 2 Þiþ hnt; ð t 3 Þi hnt; ð t 4 Þiþ... ð5aþ hpi ¼ hpt; ð t Þi hpt; ð t 2 Þiþhpt; ð t 3 Þi hpt; ð t 4 Þiþ... ð5bþ The total rift currents, for the series of Heavisie s square waves are: I n ¼ Squ n hni; ð6aþ I p ¼ Squ p hpi; ð6bþ

7 J Infrare Milli Terahz Waves wherein the mean values for concentrations are obtaine from (5a) an (5b), an iffusion current is: I if ¼ I if ðt; t Þ I if ðt; t 2 ÞþI if ðt; t 3 Þ I if ðt; t 4 Þþ... ð6cþ The last equation shows that the iffusion current, like rift currents, is obtaine by summing iffusion currents for each Heavisie s function. Now we have all the require epenencies to create the equivalent electric circuit of the P-i-N photoioe for the case of series of Heavisie s square waves (Fig. 2). The main circuit consists of the inepenent voltage generator V CC, resistance R, capacitance C t =εs/, parasitic capacitance C s, an three epenent currents sources (two for rift currents an one for iffusion current). The main circuit is obtaine from () an (3). One subcircuit solves epenence of intensity of electric fiel on the photoioe voltage. Two subcircuits solve the epenence of velocities on electric fiel, wherein functions f an f 2 are given with expressions (a) an (b). In the case of constant carriers velocities there is no nee for these subcircuits an velocities can be taken as the input parameters. Since we use them as slowly changeable there is a nee to recalculate them in the subcircuits. In accorance with (5a), (5b) an (6c) one by one subcircuit is if cc p n U(t)-V E(t) / f (E(t)) n(t) f 2 (E(t)) p(t) f 3 ( n (t),t ) n(t,t ) n(t,t 2 ) f 3 ( n (t),t 2 ) p(t,t ) f 4 ( p (t),t ) f 4 ( p (t),t 2 ) p(t,t 2 ) t s I if (t,t ) I if (t,t 2 ) f 5 (t,t ) f 5 (t,t 2 ) Fig. 2 The equivalent electric circuit of the P-i-N photoioe.

8 J Infrare Milli Terahz Waves inserte to solve carriers concentrations an iffusion current for each Heavisie s pulse (in the series of Heavisie s square waves). So we involve 2 subcircuits to resolve the electrons concentration for the case of Heavisie s square waves, together with 2 subcircuits for holes concentration, an 2 subcircuits for iffusion current. All these subcircuits use resistance of Ohm. These subcircuits solve the require carriers concentrations given within the formulas (7a) (7c) an (8a) (8c), an iffusion current given by (2). The circuit presente in Fig. 2 was ensue from the previous consierations. Completely the same circuit can be obtaine for ifferent time forms of input excitation, only the functions use in Eqs. 7a 7c an 8a 8c will iffer. The circuit is incorporate into SPICE program an the simulate results are obtaine. 3 Results an iscussion In the calculations we use next parameters of the GaAs photoioe: α= 4 cm, =5 μm, m n ¼ 75 cm2 Vs, m p ¼ 42 cm2 Vs, E M ¼ 3; 2 kv cm, v sat ¼ 8 6 cm s, R=5Ω, V =.6 V, an V CC = 5 V. Dielectric constant is ε r =2, photoioe area S=7 μm 2, an the wavelength of input excitation is l=.8 μm. It shoul be note that in all simulations holes velocity is calculate using the Eq. b. The first results presente in Fig. 3, obtaine for one Heavisie s square wave input excitation, show the ifferences in photoioe responses when saturation electrons velocity an slowly changeable electrons velocity υ sat an υ n (t) are use. The both results are obtaine using the SPICE program. In the first case, instea of the Eq. a, electrons velocity is given as the constant saturation velocity. In the secon case velocity is calculate in SPICE, in the subcircuit which solves Eq. a (subcircuit solves electron s velocity epenence on the instantaneously photoioe voltage). The ifferences obtaine in results are significant concerning the minimum of the photoioe voltage an time response. The error, occurre as a consequence of using the constant saturation electrons velocity, is about 22% comparing to the secon case. 5, photoioe voltage [V] 4, υ n = υ sat υ n (t) 3, time [ps] Fig. 3 The photoioe responses to the Heavisie s square wave, P=.5 W(h(t)-h(t- ps)), in the cases of: saturation electrons velocity an changeable electrons velocity. Both results are obtaine using SPICE program.

9 J Infrare Milli Terahz Waves (Here the time response of the photoioe is efine as a time in which photoioe voltage reaches the value of.99 V CC ). Generally the error epens on the parameters of input signal (power an time uration of the input signal). On Fig. 4 we compare the SPICE results with more exact FORTRAN results. Here FORTRAN results can be taken as exact because in FORTRAN we use Eqs. 2a an 2b with integral of photoioe voltage for overpasse path of carriers. The maximum obtaine error between SPICE an FORTRAN results is about 6%, an there is no error in the minimum of the photoioe response. So we can say that SPICE moel use here gives more accurate results than the moel with constant velocities. It is obvious that approximation use in this moel, where the overpasse path is calculate like υ(t) t, gives reliable results as long as the change of the photoioe voltage is not too high, an when the velocities can be taken as slowly changeable. It is necessary to efine the omain of input parameters where the approximation is vali. With the aim to establishing the relevant omain we analyze the maximum errors between the SPICE an FORTRAN results. The results are obtaine for one Heavisie s square wave, for ifferent input energies an ifferent time uration of the input signal, an they are presente in Fig. 5. Figure 5 inicates the increase of error (between SPICE an FORTRAN) with the increase of input energy. In the case of the same input energy, error increase for ecrease of time uration of input pulse. High input energy leas to bigger changes of velocities an, as the consequence, the obtaine error in overpasse paths is bigger. It means that higher the nonlinearity, of the working regime, the higher error is obtaine. If we efine quasi-linear working regime as a regime where the error between FORTRAN moel an SPICE moel is less than 5%, we can efine the omain of input parameters. For one pulse (one Heavisie s square wave) for the photoioe, linear working regime is obtaine for input energies less than.75 pj, an for the case of input energies between.75 pj an 2.2 pj linear working regime is obtaine if the time uration of the pulse is higher than 4 ps. The similar results, concerning the behavior of photoioe response, coul be obtaine using only SPICE program. In some segments, minimum of the photoioe response has linear epenence on the input energy as shown in Fig. 6. The photoioe response shows 5, photoioe voltage [V] 4, error=6% SPICE FORTRAN 3, time [ps] Fig. 4 The photoioe response to the Heavisie s square wave, P=.5 W(h(t)-h(t- ps)), when changeable electrons velocity is use (SPICE), an when integral of photoioe voltage is use for calculation of overpasse path of electrons (FORTRAN).

10 J Infrare Milli Terahz Waves max. error [%] E=2.2pJ 2pJ.85pJ.75pJ.5pJ pj.5pj time uration of pulse [ps] Fig. 5 The maximum error obtaine in SPICE compare to FORTRAN results. The error is the consequence of ifferences between the total path calculate in SPICE an FORTRAN. linear behavior up to the values of minimum photoioe voltage higher than 3.25 V. If the photoioe voltage minimum is lower than 3.25 V the borer of the linear epenence is exceee. So we have two ways of investigating the linearity of the case. First way is to check the values of input parameters, an secon is to check minimum of the photoioe response an its linearity. For more than one pulse, the situation is more complicate. The question is when it is possible to obtain response on the two separate light signals as a sum of two inepenent responses, an when the total response iffers from the sum of two inepenent responses. This means that now linear working regime epens on three parameters input energy, time uration of pulse an time perio between two pulses. As long as the photoioe response acts like a sum of two inepenent responses to the excitation of two inepenent light pulses we consier a working regime as the linear one. V CC -U min [V] 3, 2,5 2,,5,,5 time uration of the pulse [ps] ,,25,5,75,,25,5,75 2, 2,25 2,5 energy [pj] Fig. 6 The obtaine ifference between the bias voltage an minimum of the photoioe response for ifferent energies an time urations of pulse.

11 J Infrare Milli Terahz Waves First we obtain the total photoioe response to the two ientical input signals, an then we obtain the secon response, calculate as a sum of responses (obtaine inepenently for each pulse). Also, we have change the time perio between those two pulses. If the ifference between these two responses is less than 5% we consier the case as a linear one. For given energies, time uration of one pulse an time perio between two ientical pulses we get Fig. 7. The straight lines, in Fig. 7, inicate the minimum time, which has to pass between two pulses, for given energy an time uration of one pulse, to stay in linear regime within the error of 5%. From Fig. 7 it is obvious that minimum time between two pulses (when two ientical pulses come) has linear epenences on the uration of the pulse for a given energy. It shoul be note that the points on the straight lines in Fig. 7 are not obtaine for the same errors, but were chosen to fulfill the request that minimum error is less than 5%. The linear epenences shown in Fig. 7 coul be fitte by equation: where A epens on the input energy as: A ¼ 36:2 exp t ¼ A :35ðT 5psÞ; ð7þ E :78 :57 : ð8þ Here energy is given in [pj], an time an constant A in [ps]. So for given energy an time uration of the signal T, it is possible to fin minimum time t, between two ientical pulses, either using Fig. 7 or using formulas (7) an (8), to obtain linear working regime. If actual time between two pulses is greater than t the photoioe works in linear regime an vice versa. The example of the fact that linearity of the case epens on the time between two pulses is presente in Fig. 8. Here in the first case (lower curve) time between the pulses is ps an in the secon case it is 3 ps. Inepenently observe, both pulses put the photoioe in the linear working regime. When pulses are taken together it is possible that working regime exceees the linear one. time between two pulses [ps] E = pj E =.5pJ Numerical calculations τ = A-.35(T-5ps) E = 2pJ time uration of one pulse [ps] Fig. 7 The minimum time between two ientical pulses, in orer to achieve the linear working regime, is obtaine as a linear epenence on the time uration of one pulse. If the time between two pulses is above the corresponing straight line than it is obtaine linear working regime an vice versa.

12 J Infrare Milli Terahz Waves photoioe voltage [V] 5, 4, 3, 2,5 2,,5 sum of inepenent responses response on the sum of pulses error = % error = 9% 6, 5,5 5, 4, 3, 2,5, 2, time [ps] Fig. 8 Comparison of obtaine responses for two ientical Heavisie s square waves. The left axis refers to the upper curves, P=.2 W(h(t)-h(t-5 ps)+h(t-8 ps)-h(t-23 ps)), an right axis refers to the lower curves, P=.2 W(h(t)-h(t-5 ps)+h(t-5 ps)-h(t-2 ps)). The error in results epens on the time which passes between two input signals. In the case of two input pulses, with energies of pj an time urations of 5 ps, in Fig. 7, we fin that minimum time between pulses to stay in linear working regime is ps. So the upper curve in Fig. 8 is obtaine for linear working regime, whereas lower curve inicates that the working regime slightly excees the borers of linearity. Before explanation what happens in the case of more than two input signals, it is necessary to investigate the case of two input signals with ifferent characteristics. The results, from the observe behaviors of responses, show that Fig. 7 can be use in the similar way as it is alreay use in the case of ientical pulses. For the first input signal we fin τ. For the secon input signal we fin τ 2, an for the require time between the two signals, to enable the linear working regime, higher of these two values shoul be chosen. Here it shoul be note that it is also possible to obtain linear working regime for time less than chosen τ. But, to be sure that the selecte regime is linear, it is better to choose such more strict criteria, an it woul only result in the error less than 5%. Figure 9 is obtaine for two ifferent input signals, where the time between two signals was change. For the two signals it is calculate τ an τ 2 using the Eqs. 7 an 8. Higher value (between these two) is τ =2 ps. So the upper curves in Fig. 9 are obtaine for the time perio between two pulses equals 2 ps, an lower curves are obtaine for much shorter time perio, equals 5 ps. Consiering the error in obtaine response the upper curves belong to the linear regime whereas the lower curves inicate the nonlinear regime. So to enable linear working regime of the photoioe, the parameters of one input signal shoul be chosen in relevant omain, an the time perio between two or more signals must be appropriate. To fulfill the first eman, in case of the photoioe, the energy of input signal shoul be less than.75 pj, or for energies between.75 pj an 2.2 pj the time uration of the signal shoul be greater than 4 ps. For two signals, to stay within linear regime, time between two signals shoul be greater than calculate minimum τ (t>max(t, t 2 )). For more than two input signals, to fulfill the request for the linear working regime, it is necessary that time between each two pulses is higher than etermine τ (herewefinτ for each par of input pulses). The

13 J Infrare Milli Terahz Waves photoioe voltage [V] 5, 4, 3, 2,5 2,,5 sum of inepenent responses response on the sum of pulses error = 5% error = 2% 6, 5,5 5, 4, 3, 2,5, 2, time [ps] Fig. 9 The change of error in obtaine results epens on the time between two pulses. The left axis refers to the upper curves, P=.5 W(h(t)-h(t- ps))+. W(h(t-35 ps)-h(t-45 ps)), an right axis refers to the lower curves, P=.5 W(h(t)-h(t- ps))+. W(h(t-5 ps)-h(t-25 ps)). examples of the photoioe responses to ifferent input excitation are presente in Figs. an. Figure presents photoioe response to the series of 4 Heavisie s square waves. Each pulse inepenently observe gives linear working regime. The time perio between them is chosen to enable linear working regime. The error between presente response an the sum of inepenent responses (on each pulse) is equal to 7.5%, which is less than 5% an the request for linear regime is fulfille. Figure presents photoioe response to the series of the same Heavisie s square waves as in Fig.. Only the time perios between signals were change an it le to the error of 23%. 5, photoioe voltage [V] 4, 3, 2,5 sum of inepenent responses response on the sum of pulses error = 7.5% 2, time [ps] Fig. The response to the series of Heavisie s pulses, P=.5 W(h(t)-h(t- ps))+. W(h(t-3 ps)-h(t- 4 ps)+.5 W(h(t-45 ps)-h(t-85 ps))+. W(h(t-95 ps)-h(t- ps)).the maximum error is less than 5%. The photoioe response is linear.

14 J Infrare Milli Terahz Waves photoioe voltage [V] 5, 4, 3, 2,5 sum of inepenent responses response on the sum of pulses error = 23% 2, time [ps] Fig. The response to the series of Heavisie s pulses, P=.5 W(h(t)-h(t- ps))+. W(h(t-5 ps)-h(t- 25 ps)+.5 W(h(t-45 ps)-h(t-85 ps))+. W(h(t-9 ps)-h(t-5 ps)). The maximum error (23%) occurs in response to the first two pulses, because the time perio between them is ecrease to 5 ps instea of 2 ps (in the case of Fig. ). The photoioe working regime is nonlinear. 4 Conclusions The evelope moel, which takes into account the effect of change of carriers velocities, shows significant ifferences compare to the moels with constant velocities fin in literature, especially concerning minimum of the photoioe voltage response an time response. All results are presente as a voltage time epenences to enable the stuy of igital an signals an to show the ifferences in behavior of response. The SPICE moel is compare to erive FORTRAN moel. The ifferences in the programs results are ue to the way of calculating the overpasse path. SPICE an FORTRAN results iffer significantly for higher values of input energies, where the photoioe linear working regime is exceee. For smaller input energies, i.e. in linear an quasi-linear working regime, the results show very goo agreement. We assume that quasi-linear working regime lasts as long as the values of the instantaneous carriers velocities o not iffer significantly from the mean values. Also, concerning more than one incient pulse, linear working regime is efine as a regime where the sum of inepenent responses (to each pulse inepenently) is equal to the total response to the series of incient pulses. The total response in that case epens not only on energy an time uration of the signal pulses but also on the time between two signal pulses. All results inicate that it is practical an convenient to use this moel, an the corresponing SPICE program, whenever the input energy is not too high so we can say that photoioe is in some quasi-linear regime. Practically, whether the regime is linear or not epens on photoioe s characteristics an energy an time epenence of input excitation. For an actual photoioe, as long as minimum of the photoioe response has linear epenence on the input energy we can say that results are accurate. Results also show goo corresponence with FORTRAN results when we succee linear regime, but nonlinearity is ifficult to comment without taking into account the effect of space charge. Acknowlegments This work was supporte by the Serbian Ministry of Science an Technological Development with contract No. 6A.

15 J Infrare Milli Terahz Waves Appenix The iffusion current is obtaine using the continuity equation for holes in N region in the case of Dirac s time input D 2 p 2 þ p n p n t p ¼ ai expð axþðt t Þ: ða:þ In above equation p n is the holes concentration in N region, D p is iffusion constant for holes, τ p is the holes life time in N region, p n is the thermal-equilibrium hole s concentration in N region. Here we propose borer conitions in steay state as p n ðx ¼ W n Þ ¼ an p n ðx ¼/ Þ ¼ p no. This approximation is involve with the aim to simplify solving the case. Solution of the Eq. A. is p n ðx; tþ ¼ p n p n exp x L p þ ai expð ax Þexpð gðt t o ÞÞht ð t Þ; ða:2þ where γ=(-α 2 L 2 p )/t p, an x>. The holes iffusion current in N region can be obtaine n I pif ¼ qsd : ða:3þ x¼ Consiering that the last member in Eq. A.2 has the biggest value, we exclue the rest members an obtain I pif ¼ qsd p a 2 I expð aþexpð gðt t ÞÞ: ða:4þ Using the Eq. A.4 an parameter τ instea of (t-t ), we obtain I pif for the case of Heavisie s time input excitation as I pif ¼ qsd p a 2 ðint Þexpð aþ Z hðt t tþ expð gtþt; ða:5þ where int is the intensity of Heavisie s function. Solving the above integral we get Eq. 2. References. W. Chen, S. Liu, IEEE Journal of Quantum Electronics, vol. 32, no. 2, pp. 25, (996) 2. J. Jou, C. Liu, C. Hsiao, H. Lin an Hsiu-Chih Lee, IEEE Photonic Technology Letters, vol. 4, no. 4, pp. 525, (22) 3. Y. Batawy, J. Deen, Journal of Lightwave Technology, vol. 23, no., pp. 423, (25) 4. Y. Batawy, J. Deen, an N. Das, Journal of Lightwave Technology, vol. 2, no. 9, pp. 23, (23) 5. Y. Batawy, J. Deen, IEEE Transaction on Electron Devices, vol. 52, no. 3, pp. 325, (25) 6. M. Lu, J. Deng, C. Juang, M. Jou, an B. Lee, IEEE Journal of Quantum Electronics, vol. 3, no. 8, pp. 48, (995) 7. G. Rossi, R. Paoletti, an M. Meliga, IEEE/OSA Journal of Lightwave Technology, vol. 6, no. 8, pp. 59, (998) 8. B. Tsou, D. Pulfrey, IEEE Journal of Quantum Electronics, vol. 33, no. 2, pp. 246, (997) 9. C. Chang, H. Fetterman, Soli-state electronics, vol. 29 no. 2, pp. 295, (986). S. Malyshev, A. Chizh, Journal of Selecte Topics in Quantum Electronics, vol., no. 4, pp. 679, (24). P. Matavulj, D. Gvozić, J.Raunović, Journal of Lightwave Technology, vol. 5, no. 2, pp. 227, (997) 2. M. Lazović, P. Matavulj an J. Raunović, Microwave an Optical Technology Letters, vol. 4, no. 6, pp. 468, (24)

Chapter 2 Lagrangian Modeling

Chapter 2 Lagrangian Modeling Chapter 2 Lagrangian Moeling The basic laws of physics are use to moel every system whether it is electrical, mechanical, hyraulic, or any other energy omain. In mechanics, Newton s laws of motion provie

More information

APPROXIMATE SOLUTION FOR TRANSIENT HEAT TRANSFER IN STATIC TURBULENT HE II. B. Baudouy. CEA/Saclay, DSM/DAPNIA/STCM Gif-sur-Yvette Cedex, France

APPROXIMATE SOLUTION FOR TRANSIENT HEAT TRANSFER IN STATIC TURBULENT HE II. B. Baudouy. CEA/Saclay, DSM/DAPNIA/STCM Gif-sur-Yvette Cedex, France APPROXIMAE SOLUION FOR RANSIEN HEA RANSFER IN SAIC URBULEN HE II B. Bauouy CEA/Saclay, DSM/DAPNIA/SCM 91191 Gif-sur-Yvette Ceex, France ABSRAC Analytical solution in one imension of the heat iffusion equation

More information

Homework 7 Due 18 November at 6:00 pm

Homework 7 Due 18 November at 6:00 pm Homework 7 Due 18 November at 6:00 pm 1. Maxwell s Equations Quasi-statics o a An air core, N turn, cylinrical solenoi of length an raius a, carries a current I Io cos t. a. Using Ampere s Law, etermine

More information

Modeling time-varying storage components in PSpice

Modeling time-varying storage components in PSpice Moeling time-varying storage components in PSpice Dalibor Biolek, Zenek Kolka, Viera Biolkova Dept. of EE, FMT, University of Defence Brno, Czech Republic Dept. of Microelectronics/Raioelectronics, FEEC,

More information

Thermal conductivity of graded composites: Numerical simulations and an effective medium approximation

Thermal conductivity of graded composites: Numerical simulations and an effective medium approximation JOURNAL OF MATERIALS SCIENCE 34 (999)5497 5503 Thermal conuctivity of grae composites: Numerical simulations an an effective meium approximation P. M. HUI Department of Physics, The Chinese University

More information

05 The Continuum Limit and the Wave Equation

05 The Continuum Limit and the Wave Equation Utah State University DigitalCommons@USU Founations of Wave Phenomena Physics, Department of 1-1-2004 05 The Continuum Limit an the Wave Equation Charles G. Torre Department of Physics, Utah State University,

More information

6. Friction and viscosity in gasses

6. Friction and viscosity in gasses IR2 6. Friction an viscosity in gasses 6.1 Introuction Similar to fluis, also for laminar flowing gases Newtons s friction law hols true (see experiment IR1). Using Newton s law the viscosity of air uner

More information

Conservation laws a simple application to the telegraph equation

Conservation laws a simple application to the telegraph equation J Comput Electron 2008 7: 47 51 DOI 10.1007/s10825-008-0250-2 Conservation laws a simple application to the telegraph equation Uwe Norbrock Reinhol Kienzler Publishe online: 1 May 2008 Springer Scienceusiness

More information

Schrödinger s equation.

Schrödinger s equation. Physics 342 Lecture 5 Schröinger s Equation Lecture 5 Physics 342 Quantum Mechanics I Wenesay, February 3r, 2010 Toay we iscuss Schröinger s equation an show that it supports the basic interpretation of

More information

THE VAN KAMPEN EXPANSION FOR LINKED DUFFING LINEAR OSCILLATORS EXCITED BY COLORED NOISE

THE VAN KAMPEN EXPANSION FOR LINKED DUFFING LINEAR OSCILLATORS EXCITED BY COLORED NOISE Journal of Soun an Vibration (1996) 191(3), 397 414 THE VAN KAMPEN EXPANSION FOR LINKED DUFFING LINEAR OSCILLATORS EXCITED BY COLORED NOISE E. M. WEINSTEIN Galaxy Scientific Corporation, 2500 English Creek

More information

Calculus of Variations

Calculus of Variations Calculus of Variations Lagrangian formalism is the main tool of theoretical classical mechanics. Calculus of Variations is a part of Mathematics which Lagrangian formalism is base on. In this section,

More information

6 General properties of an autonomous system of two first order ODE

6 General properties of an autonomous system of two first order ODE 6 General properties of an autonomous system of two first orer ODE Here we embark on stuying the autonomous system of two first orer ifferential equations of the form ẋ 1 = f 1 (, x 2 ), ẋ 2 = f 2 (, x

More information

PRACTICE 4. CHARGING AND DISCHARGING A CAPACITOR

PRACTICE 4. CHARGING AND DISCHARGING A CAPACITOR PRACTICE 4. CHARGING AND DISCHARGING A CAPACITOR. THE PARALLEL-PLATE CAPACITOR. The Parallel plate capacitor is a evice mae up by two conuctor parallel plates with total influence between them (the surface

More information

Computing Exact Confidence Coefficients of Simultaneous Confidence Intervals for Multinomial Proportions and their Functions

Computing Exact Confidence Coefficients of Simultaneous Confidence Intervals for Multinomial Proportions and their Functions Working Paper 2013:5 Department of Statistics Computing Exact Confience Coefficients of Simultaneous Confience Intervals for Multinomial Proportions an their Functions Shaobo Jin Working Paper 2013:5

More information

Table of Common Derivatives By David Abraham

Table of Common Derivatives By David Abraham Prouct an Quotient Rules: Table of Common Derivatives By Davi Abraham [ f ( g( ] = [ f ( ] g( + f ( [ g( ] f ( = g( [ f ( ] g( g( f ( [ g( ] Trigonometric Functions: sin( = cos( cos( = sin( tan( = sec

More information

1 Heisenberg Representation

1 Heisenberg Representation 1 Heisenberg Representation What we have been ealing with so far is calle the Schröinger representation. In this representation, operators are constants an all the time epenence is carrie by the states.

More information

State-Space Model for a Multi-Machine System

State-Space Model for a Multi-Machine System State-Space Moel for a Multi-Machine System These notes parallel section.4 in the text. We are ealing with classically moele machines (IEEE Type.), constant impeance loas, an a network reuce to its internal

More information

Chapter 11: Feedback and PID Control Theory

Chapter 11: Feedback and PID Control Theory Chapter 11: Feeback an D Control Theory Chapter 11: Feeback an D Control Theory. ntrouction Feeback is a mechanism for regulating a physical system so that it maintains a certain state. Feeback works by

More information

Lagrangian and Hamiltonian Mechanics

Lagrangian and Hamiltonian Mechanics Lagrangian an Hamiltonian Mechanics.G. Simpson, Ph.. epartment of Physical Sciences an Engineering Prince George s Community College ecember 5, 007 Introuction In this course we have been stuying classical

More information

Quantum mechanical approaches to the virial

Quantum mechanical approaches to the virial Quantum mechanical approaches to the virial S.LeBohec Department of Physics an Astronomy, University of Utah, Salt Lae City, UT 84112, USA Date: June 30 th 2015 In this note, we approach the virial from

More information

Separation of Variables

Separation of Variables Physics 342 Lecture 1 Separation of Variables Lecture 1 Physics 342 Quantum Mechanics I Monay, January 25th, 2010 There are three basic mathematical tools we nee, an then we can begin working on the physical

More information

Vectors in two dimensions

Vectors in two dimensions Vectors in two imensions Until now, we have been working in one imension only The main reason for this is to become familiar with the main physical ieas like Newton s secon law, without the aitional complication

More information

Chapter 11: Feedback and PID Control Theory

Chapter 11: Feedback and PID Control Theory Chapter 11: Feeback an D Control Theory Chapter 11: Feeback an D Control Theory. ntrouction Feeback is a mechanism for regulating a physical system so that it maintains a certain state. Feeback works by

More information

ensembles When working with density operators, we can use this connection to define a generalized Bloch vector: v x Tr x, v y Tr y

ensembles When working with density operators, we can use this connection to define a generalized Bloch vector: v x Tr x, v y Tr y Ph195a lecture notes, 1/3/01 Density operators for spin- 1 ensembles So far in our iscussion of spin- 1 systems, we have restricte our attention to the case of pure states an Hamiltonian evolution. Toay

More information

An inductance lookup table application for analysis of reluctance stepper motor model

An inductance lookup table application for analysis of reluctance stepper motor model ARCHIVES OF ELECTRICAL ENGINEERING VOL. 60(), pp. 5- (0) DOI 0.478/ v07-0-000-y An inuctance lookup table application for analysis of reluctance stepper motor moel JAKUB BERNAT, JAKUB KOŁOTA, SŁAWOMIR

More information

An analytical investigation into filmwise condensation on a horizontal tube in a porous medium with suction at the tube surface

An analytical investigation into filmwise condensation on a horizontal tube in a porous medium with suction at the tube surface Heat Mass Transfer (29) 45:355 361 DOI 1.17/s231-8-436-y ORIGINAL An analytical investigation into filmwise conensation on a horizontal tube in a porous meium with suction at the tube surface Tong Bou

More information

Polynomial Inclusion Functions

Polynomial Inclusion Functions Polynomial Inclusion Functions E. e Weert, E. van Kampen, Q. P. Chu, an J. A. Muler Delft University of Technology, Faculty of Aerospace Engineering, Control an Simulation Division E.eWeert@TUDelft.nl

More information

Chapter 6: Energy-Momentum Tensors

Chapter 6: Energy-Momentum Tensors 49 Chapter 6: Energy-Momentum Tensors This chapter outlines the general theory of energy an momentum conservation in terms of energy-momentum tensors, then applies these ieas to the case of Bohm's moel.

More information

Chapter 2 Governing Equations

Chapter 2 Governing Equations Chapter 2 Governing Equations In the present an the subsequent chapters, we shall, either irectly or inirectly, be concerne with the bounary-layer flow of an incompressible viscous flui without any involvement

More information

Introduction to the Vlasov-Poisson system

Introduction to the Vlasov-Poisson system Introuction to the Vlasov-Poisson system Simone Calogero 1 The Vlasov equation Consier a particle with mass m > 0. Let x(t) R 3 enote the position of the particle at time t R an v(t) = ẋ(t) = x(t)/t its

More information

A Novel Decoupled Iterative Method for Deep-Submicron MOSFET RF Circuit Simulation

A Novel Decoupled Iterative Method for Deep-Submicron MOSFET RF Circuit Simulation A Novel ecouple Iterative Metho for eep-submicron MOSFET RF Circuit Simulation CHUAN-SHENG WANG an YIMING LI epartment of Mathematics, National Tsing Hua University, National Nano evice Laboratories, an

More information

SYNCHRONOUS SEQUENTIAL CIRCUITS

SYNCHRONOUS SEQUENTIAL CIRCUITS CHAPTER SYNCHRONOUS SEUENTIAL CIRCUITS Registers an counters, two very common synchronous sequential circuits, are introuce in this chapter. Register is a igital circuit for storing information. Contents

More information

Sensors & Transducers 2015 by IFSA Publishing, S. L.

Sensors & Transducers 2015 by IFSA Publishing, S. L. Sensors & Transucers, Vol. 184, Issue 1, January 15, pp. 53-59 Sensors & Transucers 15 by IFSA Publishing, S. L. http://www.sensorsportal.com Non-invasive an Locally Resolve Measurement of Soun Velocity

More information

Math 342 Partial Differential Equations «Viktor Grigoryan

Math 342 Partial Differential Equations «Viktor Grigoryan Math 342 Partial Differential Equations «Viktor Grigoryan 6 Wave equation: solution In this lecture we will solve the wave equation on the entire real line x R. This correspons to a string of infinite

More information

inflow outflow Part I. Regular tasks for MAE598/494 Task 1

inflow outflow Part I. Regular tasks for MAE598/494 Task 1 MAE 494/598, Fall 2016 Project #1 (Regular tasks = 20 points) Har copy of report is ue at the start of class on the ue ate. The rules on collaboration will be release separately. Please always follow the

More information

Dynamics of the synchronous machine

Dynamics of the synchronous machine ELEC0047 - Power system ynamics, control an stability Dynamics of the synchronous machine Thierry Van Cutsem t.vancutsem@ulg.ac.be www.montefiore.ulg.ac.be/~vct These slies follow those presente in course

More information

Lower Bounds for the Smoothed Number of Pareto optimal Solutions

Lower Bounds for the Smoothed Number of Pareto optimal Solutions Lower Bouns for the Smoothe Number of Pareto optimal Solutions Tobias Brunsch an Heiko Röglin Department of Computer Science, University of Bonn, Germany brunsch@cs.uni-bonn.e, heiko@roeglin.org Abstract.

More information

Implicit Differentiation

Implicit Differentiation Implicit Differentiation Thus far, the functions we have been concerne with have been efine explicitly. A function is efine explicitly if the output is given irectly in terms of the input. For instance,

More information

Two Dimensional Numerical Simulator for Modeling NDC Region in SNDC Devices

Two Dimensional Numerical Simulator for Modeling NDC Region in SNDC Devices Journal of Physics: Conference Series PAPER OPEN ACCESS Two Dimensional Numerical Simulator for Moeling NDC Region in SNDC Devices To cite this article: Dheeraj Kumar Sinha et al 2016 J. Phys.: Conf. Ser.

More information

Optimization of Geometries by Energy Minimization

Optimization of Geometries by Energy Minimization Optimization of Geometries by Energy Minimization by Tracy P. Hamilton Department of Chemistry University of Alabama at Birmingham Birmingham, AL 3594-140 hamilton@uab.eu Copyright Tracy P. Hamilton, 1997.

More information

TMA 4195 Matematisk modellering Exam Tuesday December 16, :00 13:00 Problems and solution with additional comments

TMA 4195 Matematisk modellering Exam Tuesday December 16, :00 13:00 Problems and solution with additional comments Problem F U L W D g m 3 2 s 2 0 0 0 0 2 kg 0 0 0 0 0 0 Table : Dimension matrix TMA 495 Matematisk moellering Exam Tuesay December 6, 2008 09:00 3:00 Problems an solution with aitional comments The necessary

More information

θ x = f ( x,t) could be written as

θ x = f ( x,t) could be written as 9. Higher orer PDEs as systems of first-orer PDEs. Hyperbolic systems. For PDEs, as for ODEs, we may reuce the orer by efining new epenent variables. For example, in the case of the wave equation, (1)

More information

Chapter 11: Feedback and PID Control Theory

Chapter 11: Feedback and PID Control Theory Chapter 11: Feeback an ID Control Theory Chapter 11: Feeback an ID Control Theory I. Introuction Feeback is a mechanism for regulating a physical system so that it maintains a certain state. Feeback works

More information

Analytic Scaling Formulas for Crossed Laser Acceleration in Vacuum

Analytic Scaling Formulas for Crossed Laser Acceleration in Vacuum October 6, 4 ARDB Note Analytic Scaling Formulas for Crosse Laser Acceleration in Vacuum Robert J. Noble Stanfor Linear Accelerator Center, Stanfor University 575 San Hill Roa, Menlo Park, California 945

More information

1 dx. where is a large constant, i.e., 1, (7.6) and Px is of the order of unity. Indeed, if px is given by (7.5), the inequality (7.

1 dx. where is a large constant, i.e., 1, (7.6) and Px is of the order of unity. Indeed, if px is given by (7.5), the inequality (7. Lectures Nine an Ten The WKB Approximation The WKB metho is a powerful tool to obtain solutions for many physical problems It is generally applicable to problems of wave propagation in which the frequency

More information

x f(x) x f(x) approaching 1 approaching 0.5 approaching 1 approaching 0.

x f(x) x f(x) approaching 1 approaching 0.5 approaching 1 approaching 0. Engineering Mathematics 2 26 February 2014 Limits of functions Consier the function 1 f() = 1. The omain of this function is R + \ {1}. The function is not efine at 1. What happens when is close to 1?

More information

A simple model for the small-strain behaviour of soils

A simple model for the small-strain behaviour of soils A simple moel for the small-strain behaviour of soils José Jorge Naer Department of Structural an Geotechnical ngineering, Polytechnic School, University of São Paulo 05508-900, São Paulo, Brazil, e-mail:

More information

The Exact Form and General Integrating Factors

The Exact Form and General Integrating Factors 7 The Exact Form an General Integrating Factors In the previous chapters, we ve seen how separable an linear ifferential equations can be solve using methos for converting them to forms that can be easily

More information

CHARACTERISTICS OF A DYNAMIC PRESSURE GENERATOR BASED ON LOUDSPEAKERS. Jože Kutin *, Ivan Bajsić

CHARACTERISTICS OF A DYNAMIC PRESSURE GENERATOR BASED ON LOUDSPEAKERS. Jože Kutin *, Ivan Bajsić Sensors an Actuators A: Physical 168 (211) 149-154 oi: 1.116/j.sna.211..7 211 Elsevier B.V. CHARACTERISTICS OF A DYNAMIC PRESSURE GENERATOR BASED ON LOUDSPEAKERS Jože Kutin *, Ivan Bajsić Laboratory of

More information

24th European Photovoltaic Solar Energy Conference, September 2009, Hamburg, Germany

24th European Photovoltaic Solar Energy Conference, September 2009, Hamburg, Germany 4th European hotovoltaic Solar Energy Conference, 1-5 September 9, Hamburg, Germany LOCK-IN THERMOGRAHY ON CRYSTALLINE SILICON ON GLASS (CSG) THIN FILM MODULES: INFLUENCE OF ELTIER CONTRIBUTIONS H. Straube,

More information

MA 2232 Lecture 08 - Review of Log and Exponential Functions and Exponential Growth

MA 2232 Lecture 08 - Review of Log and Exponential Functions and Exponential Growth MA 2232 Lecture 08 - Review of Log an Exponential Functions an Exponential Growth Friay, February 2, 2018. Objectives: Review log an exponential functions, their erivative an integration formulas. Exponential

More information

APPPHYS 217 Thursday 8 April 2010

APPPHYS 217 Thursday 8 April 2010 APPPHYS 7 Thursay 8 April A&M example 6: The ouble integrator Consier the motion of a point particle in D with the applie force as a control input This is simply Newton s equation F ma with F u : t q q

More information

The derivative of a function f(x) is another function, defined in terms of a limiting expression: f(x + δx) f(x)

The derivative of a function f(x) is another function, defined in terms of a limiting expression: f(x + δx) f(x) Y. D. Chong (2016) MH2801: Complex Methos for the Sciences 1. Derivatives The erivative of a function f(x) is another function, efine in terms of a limiting expression: f (x) f (x) lim x δx 0 f(x + δx)

More information

How the potentials in different gauges yield the same retarded electric and magnetic fields

How the potentials in different gauges yield the same retarded electric and magnetic fields How the potentials in ifferent gauges yiel the same retare electric an magnetic fiels José A. Heras a Departamento e Física, E. S. F. M., Instituto Politécnico Nacional, México D. F. México an Department

More information

Transmission Line Matrix (TLM) network analogues of reversible trapping processes Part B: scaling and consistency

Transmission Line Matrix (TLM) network analogues of reversible trapping processes Part B: scaling and consistency Transmission Line Matrix (TLM network analogues of reversible trapping processes Part B: scaling an consistency Donar e Cogan * ANC Eucation, 308-310.A. De Mel Mawatha, Colombo 3, Sri Lanka * onarecogan@gmail.com

More information

Generalization of the persistent random walk to dimensions greater than 1

Generalization of the persistent random walk to dimensions greater than 1 PHYSICAL REVIEW E VOLUME 58, NUMBER 6 DECEMBER 1998 Generalization of the persistent ranom walk to imensions greater than 1 Marián Boguñá, Josep M. Porrà, an Jaume Masoliver Departament e Física Fonamental,

More information

Calculus in the AP Physics C Course The Derivative

Calculus in the AP Physics C Course The Derivative Limits an Derivatives Calculus in the AP Physics C Course The Derivative In physics, the ieas of the rate change of a quantity (along with the slope of a tangent line) an the area uner a curve are essential.

More information

Lectures - Week 10 Introduction to Ordinary Differential Equations (ODES) First Order Linear ODEs

Lectures - Week 10 Introduction to Ordinary Differential Equations (ODES) First Order Linear ODEs Lectures - Week 10 Introuction to Orinary Differential Equations (ODES) First Orer Linear ODEs When stuying ODEs we are consiering functions of one inepenent variable, e.g., f(x), where x is the inepenent

More information

x f(x) x f(x) approaching 1 approaching 0.5 approaching 1 approaching 0.

x f(x) x f(x) approaching 1 approaching 0.5 approaching 1 approaching 0. Engineering Mathematics 2 26 February 2014 Limits of functions Consier the function 1 f() = 1. The omain of this function is R + \ {1}. The function is not efine at 1. What happens when is close to 1?

More information

Lecture 10 Notes, Electromagnetic Theory II Dr. Christopher S. Baird, faculty.uml.edu/cbaird University of Massachusetts Lowell

Lecture 10 Notes, Electromagnetic Theory II Dr. Christopher S. Baird, faculty.uml.edu/cbaird University of Massachusetts Lowell Lecture 10 Notes, Electromagnetic Theory II Dr. Christopher S. Bair, faculty.uml.eu/cbair University of Massachusetts Lowell 1. Pre-Einstein Relativity - Einstein i not invent the concept of relativity,

More information

Chapter 11: Feedback and PID Control Theory

Chapter 11: Feedback and PID Control Theory Chapter 11: Feeback an D Control Theory Chapter 11: Feeback an D Control Theory. ntrouction Feeback is a mechanism for regulating a physical system so that it maintains a certain state. Feeback works by

More information

. Using a multinomial model gives us the following equation for P d. , with respect to same length term sequences.

. Using a multinomial model gives us the following equation for P d. , with respect to same length term sequences. S 63 Lecture 8 2/2/26 Lecturer Lillian Lee Scribes Peter Babinski, Davi Lin Basic Language Moeling Approach I. Special ase of LM-base Approach a. Recap of Formulas an Terms b. Fixing θ? c. About that Multinomial

More information

Short Intro to Coordinate Transformation

Short Intro to Coordinate Transformation Short Intro to Coorinate Transformation 1 A Vector A vector can basically be seen as an arrow in space pointing in a specific irection with a specific length. The following problem arises: How o we represent

More information

An Approach for Design of Multi-element USBL Systems

An Approach for Design of Multi-element USBL Systems An Approach for Design of Multi-element USBL Systems MIKHAIL ARKHIPOV Department of Postgrauate Stuies Technological University of the Mixteca Carretera a Acatlima Km. 2.5 Huajuapan e Leon Oaxaca 69000

More information

PARALLEL-PLATE CAPACITATOR

PARALLEL-PLATE CAPACITATOR Physics Department Electric an Magnetism Laboratory PARALLEL-PLATE CAPACITATOR 1. Goal. The goal of this practice is the stuy of the electric fiel an electric potential insie a parallelplate capacitor.

More information

Chapter 4. Electrostatics of Macroscopic Media

Chapter 4. Electrostatics of Macroscopic Media Chapter 4. Electrostatics of Macroscopic Meia 4.1 Multipole Expansion Approximate potentials at large istances 3 x' x' (x') x x' x x Fig 4.1 We consier the potential in the far-fiel region (see Fig. 4.1

More information

On Characterizing the Delay-Performance of Wireless Scheduling Algorithms

On Characterizing the Delay-Performance of Wireless Scheduling Algorithms On Characterizing the Delay-Performance of Wireless Scheuling Algorithms Xiaojun Lin Center for Wireless Systems an Applications School of Electrical an Computer Engineering, Purue University West Lafayette,

More information

MULTI-SCALE METHODS FOR THE SOLUTION OF THE RADIATIVE TRANSFER EQUATION

MULTI-SCALE METHODS FOR THE SOLUTION OF THE RADIATIVE TRANSFER EQUATION MULTI-SCALE METHODS FOR THE SOLUTION OF THE RADIATIVE TRANSFER EQUATION Pero J. Coelho *,, Nicolas Crouseilles **, Pero Pereira * an Maxime Roger *** * LAETA, IDMEC, Dept. of Mechanical Engineering, Instituto

More information

A Simple Model for the Calculation of Plasma Impedance in Atmospheric Radio Frequency Discharges

A Simple Model for the Calculation of Plasma Impedance in Atmospheric Radio Frequency Discharges Plasma Science an Technology, Vol.16, No.1, Oct. 214 A Simple Moel for the Calculation of Plasma Impeance in Atmospheric Raio Frequency Discharges GE Lei ( ) an ZHANG Yuantao ( ) Shanong Provincial Key

More information

PCCP PAPER. 1 Introduction. A. Nenning,* A. K. Opitz, T. M. Huber and J. Fleig. View Article Online View Journal View Issue

PCCP PAPER. 1 Introduction. A. Nenning,* A. K. Opitz, T. M. Huber and J. Fleig. View Article Online View Journal View Issue PAPER View Article Online View Journal View Issue Cite this: Phys. Chem. Chem. Phys., 2014, 16, 22321 Receive 4th June 2014, Accepte 3r September 2014 DOI: 10.1039/c4cp02467b www.rsc.org/pccp 1 Introuction

More information

Alpha Particle scattering

Alpha Particle scattering Introuction Alpha Particle scattering Revise Jan. 11, 014 In this lab you will stuy the interaction of α-particles ( 4 He) with matter, in particular energy loss an elastic scattering from a gol target

More information

The Principle of Least Action

The Principle of Least Action Chapter 7. The Principle of Least Action 7.1 Force Methos vs. Energy Methos We have so far stuie two istinct ways of analyzing physics problems: force methos, basically consisting of the application of

More information

arxiv:physics/ v2 [physics.ed-ph] 23 Sep 2003

arxiv:physics/ v2 [physics.ed-ph] 23 Sep 2003 Mass reistribution in variable mass systems Célia A. e Sousa an Vítor H. Rorigues Departamento e Física a Universiae e Coimbra, P-3004-516 Coimbra, Portugal arxiv:physics/0211075v2 [physics.e-ph] 23 Sep

More information

Situation awareness of power system based on static voltage security region

Situation awareness of power system based on static voltage security region The 6th International Conference on Renewable Power Generation (RPG) 19 20 October 2017 Situation awareness of power system base on static voltage security region Fei Xiao, Zi-Qing Jiang, Qian Ai, Ran

More information

Harmonic Modelling of Thyristor Bridges using a Simplified Time Domain Method

Harmonic Modelling of Thyristor Bridges using a Simplified Time Domain Method 1 Harmonic Moelling of Thyristor Briges using a Simplifie Time Domain Metho P. W. Lehn, Senior Member IEEE, an G. Ebner Abstract The paper presents time omain methos for harmonic analysis of a 6-pulse

More information

ELEC3114 Control Systems 1

ELEC3114 Control Systems 1 ELEC34 Control Systems Linear Systems - Moelling - Some Issues Session 2, 2007 Introuction Linear systems may be represente in a number of ifferent ways. Figure shows the relationship between various representations.

More information

PHY 114 Summer 2009 Final Exam Solutions

PHY 114 Summer 2009 Final Exam Solutions PHY 4 Summer 009 Final Exam Solutions Conceptual Question : A spherical rubber balloon has a charge uniformly istribute over its surface As the balloon is inflate, how oes the electric fiel E vary (a)

More information

Role of parameters in the stochastic dynamics of a stick-slip oscillator

Role of parameters in the stochastic dynamics of a stick-slip oscillator Proceeing Series of the Brazilian Society of Applie an Computational Mathematics, v. 6, n. 1, 218. Trabalho apresentao no XXXVII CNMAC, S.J. os Campos - SP, 217. Proceeing Series of the Brazilian Society

More information

Conservation Laws. Chapter Conservation of Energy

Conservation Laws. Chapter Conservation of Energy 20 Chapter 3 Conservation Laws In orer to check the physical consistency of the above set of equations governing Maxwell-Lorentz electroynamics [(2.10) an (2.12) or (1.65) an (1.68)], we examine the action

More information

CAPACITANCE: CHAPTER 24. ELECTROSTATIC ENERGY and CAPACITANCE. Capacitance and capacitors Storage of electrical energy. + Example: A charged spherical

CAPACITANCE: CHAPTER 24. ELECTROSTATIC ENERGY and CAPACITANCE. Capacitance and capacitors Storage of electrical energy. + Example: A charged spherical CAPACITANCE: CHAPTER 24 ELECTROSTATIC ENERGY an CAPACITANCE Capacitance an capacitors Storage of electrical energy Energy ensity of an electric fiel Combinations of capacitors In parallel In series Dielectrics

More information

Lie symmetry and Mei conservation law of continuum system

Lie symmetry and Mei conservation law of continuum system Chin. Phys. B Vol. 20, No. 2 20 020 Lie symmetry an Mei conservation law of continuum system Shi Shen-Yang an Fu Jing-Li Department of Physics, Zhejiang Sci-Tech University, Hangzhou 3008, China Receive

More information

PHYS 414 Problem Set 2: Turtles all the way down

PHYS 414 Problem Set 2: Turtles all the way down PHYS 414 Problem Set 2: Turtles all the way own This problem set explores the common structure of ynamical theories in statistical physics as you pass from one length an time scale to another. Brownian

More information

Time-of-Arrival Estimation in Non-Line-Of-Sight Environments

Time-of-Arrival Estimation in Non-Line-Of-Sight Environments 2 Conference on Information Sciences an Systems, The Johns Hopkins University, March 2, 2 Time-of-Arrival Estimation in Non-Line-Of-Sight Environments Sinan Gezici, Hisashi Kobayashi an H. Vincent Poor

More information

Assignment 1. g i (x 1,..., x n ) dx i = 0. i=1

Assignment 1. g i (x 1,..., x n ) dx i = 0. i=1 Assignment 1 Golstein 1.4 The equations of motion for the rolling isk are special cases of general linear ifferential equations of constraint of the form g i (x 1,..., x n x i = 0. i=1 A constraint conition

More information

UNIT 4:Capacitors and Dielectric

UNIT 4:Capacitors and Dielectric UNIT 4:apacitors an Dielectric SF7 4. apacitor A capacitor is a evice that is capable of storing electric charges or electric potential energy. It is consist of two conucting plates separate by a small

More information

Dusty Plasma Void Dynamics in Unmoving and Moving Flows

Dusty Plasma Void Dynamics in Unmoving and Moving Flows 7 TH EUROPEAN CONFERENCE FOR AERONAUTICS AND SPACE SCIENCES (EUCASS) Dusty Plasma Voi Dynamics in Unmoving an Moving Flows O.V. Kravchenko*, O.A. Azarova**, an T.A. Lapushkina*** *Scientific an Technological

More information

TEST 2 (PHY 250) Figure Figure P26.21

TEST 2 (PHY 250) Figure Figure P26.21 TEST 2 (PHY 250) 1. a) Write the efinition (in a full sentence) of electric potential. b) What is a capacitor? c) Relate the electric torque, exerte on a molecule in a uniform electric fiel, with the ipole

More information

Code_Aster. Detection of the singularities and calculation of a map of size of elements

Code_Aster. Detection of the singularities and calculation of a map of size of elements Titre : Détection es singularités et calcul une carte [...] Date : 0/0/0 Page : /6 Responsable : DLMAS Josselin Clé : R4.0.04 Révision : Detection of the singularities an calculation of a map of size of

More information

Nonlinear Adaptive Ship Course Tracking Control Based on Backstepping and Nussbaum Gain

Nonlinear Adaptive Ship Course Tracking Control Based on Backstepping and Nussbaum Gain Nonlinear Aaptive Ship Course Tracking Control Base on Backstepping an Nussbaum Gain Jialu Du, Chen Guo Abstract A nonlinear aaptive controller combining aaptive Backstepping algorithm with Nussbaum gain

More information

IPMSM Inductances Calculation Using FEA

IPMSM Inductances Calculation Using FEA X International Symposium on Inustrial Electronics INDEL 24, Banja Luka, November 68, 24 IPMSM Inuctances Calculation Using FEA Dejan G. Jerkan, Marko A. Gecić an Darko P. Marčetić Department for Power,

More information

3.7 Implicit Differentiation -- A Brief Introduction -- Student Notes

3.7 Implicit Differentiation -- A Brief Introduction -- Student Notes Fin these erivatives of these functions: y.7 Implicit Differentiation -- A Brief Introuction -- Stuent Notes tan y sin tan = sin y e = e = Write the inverses of these functions: y tan y sin How woul we

More information

LeChatelier Dynamics

LeChatelier Dynamics LeChatelier Dynamics Robert Gilmore Physics Department, Drexel University, Philaelphia, Pennsylvania 1914, USA (Date: June 12, 28, Levine Birthay Party: To be submitte.) Dynamics of the relaxation of a

More information

Linear First-Order Equations

Linear First-Order Equations 5 Linear First-Orer Equations Linear first-orer ifferential equations make up another important class of ifferential equations that commonly arise in applications an are relatively easy to solve (in theory)

More information

1. The electron volt is a measure of (A) charge (B) energy (C) impulse (D) momentum (E) velocity

1. The electron volt is a measure of (A) charge (B) energy (C) impulse (D) momentum (E) velocity AP Physics Multiple Choice Practice Electrostatics 1. The electron volt is a measure of (A) charge (B) energy (C) impulse (D) momentum (E) velocity. A soli conucting sphere is given a positive charge Q.

More information

Extinction, σ/area. Energy (ev) D = 20 nm. t = 1.5 t 0. t = t 0

Extinction, σ/area. Energy (ev) D = 20 nm. t = 1.5 t 0. t = t 0 Extinction, σ/area 1.5 1.0 t = t 0 t = 0.7 t 0 t = t 0 t = 1.3 t 0 t = 1.5 t 0 0.7 0.9 1.1 Energy (ev) = 20 nm t 1.3 Supplementary Figure 1: Plasmon epenence on isk thickness. We show classical calculations

More information

Chapter 9 Method of Weighted Residuals

Chapter 9 Method of Weighted Residuals Chapter 9 Metho of Weighte Resiuals 9- Introuction Metho of Weighte Resiuals (MWR) is an approimate technique for solving bounary value problems. It utilizes a trial functions satisfying the prescribe

More information

Final Exam Study Guide and Practice Problems Solutions

Final Exam Study Guide and Practice Problems Solutions Final Exam Stuy Guie an Practice Problems Solutions Note: These problems are just some of the types of problems that might appear on the exam. However, to fully prepare for the exam, in aition to making

More information

Linear and quadratic approximation

Linear and quadratic approximation Linear an quaratic approximation November 11, 2013 Definition: Suppose f is a function that is ifferentiable on an interval I containing the point a. The linear approximation to f at a is the linear function

More information

PHYSICS BASED CHARGE AND DRAIN CURRENT MODEL FOR AlGaN/GaN HEMT DEVICES

PHYSICS BASED CHARGE AND DRAIN CURRENT MODEL FOR AlGaN/GaN HEMT DEVICES Journal of Electron Devices, ol. 14, 01, pp. 1155-1160 JED [ISSN: 168-347 ] PHYSICS BASED CHARGE AND DRAIN CURRENT MODEL FOR AlGaN/GaN HEMT DEICES Gowin Raj 1, Hemant Pareshi 1, Suhansu Kumar Pati 1, N

More information

arxiv: v1 [physics.flu-dyn] 8 May 2014

arxiv: v1 [physics.flu-dyn] 8 May 2014 Energetics of a flui uner the Boussinesq approximation arxiv:1405.1921v1 [physics.flu-yn] 8 May 2014 Kiyoshi Maruyama Department of Earth an Ocean Sciences, National Defense Acaemy, Yokosuka, Kanagawa

More information