Yu.S.Tsyganov FLNR, JINR Statistical model of PIPS detector operating in a real-time mode. Yu.S.Tsyganov FLNR, JINR Content 1)Introduction Synthesis of.

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Yu.S.Tsyganov FLNR, JINR Statistical model of PIPS detector operating in a real-time mode. Yu.S.Tsyganov FLNR, JINR Content 1)Introduction Synthesis of SHE at the Dubna Gas-filled Recoil, PIPS detector, EVR-α(n)-SF correlations…technical systems..etc. 2) Active correlations technique – radical suppression of beam associated backgrounds a) Idea; b) Algorithm for PIPS position sensitive detector, realization ; c) Statistical analysis of the candidate to event measured with the mentioned method 3) Summary Yu.Tsyganov 08 Sept. NEC’2009 Varna, Bulgaria Target wheel mounting

* *... Experiment 226 Ra+ 48 Ca  270 Hs+4n DGFRS, 2008 The Dubna Gas –Filled recoil Separator (JINR+LLNL since ~2001) GSI, RIKEN Radioactive target design ( six sectors), Foil – 1.5 mcm Ti.

DGFRS + Detection module

DGFRS+ Backgrounds ( a few words ) Maim advantage of Gas Field separators – transport efficiency Everything else : drawbacks. eg. Separation high cyclotron vacuum and working volume of the separator, separation working area of the separator and TOF module (vacuum or pentane..), is not easy to provide linear measurement of the beam dose (cross section?), high intensity beam stop is near 2-3 m with respect to detection module etc..etc) (!) especially : there are backgrounds in the beam On phase imitating well α-decays, that is, creating no signal in TOF module DETECTION in real-time mode a candidate to ER –α chain is suppress radically such a background and provide a minimum loss in the whole efficiency (units of prc -10%) Main histogram – spectrum with suppression both TOF and VETO detector. Right hand tail is evident. Whereas, right-upper corner histogram is with real-time detection of ER-alpha chains

Real-time algorithm ( in brief. In details – my report at NEC Nucl. Inst.&Meth. A513(2003), A558(2006), A 525(2004), A573(2007), A477(2002), J.Phys. G. 25(1999)937) last versions: PSD-7 conf. (Liverpool, UK(2005)sept., & 6 th Balkan Phys. Union Conf., Istanbul (2006) sept.) idea: Yu.S. Tsyganov (NEC’97 (Sept., VARNA, Bulgaria) +HPC’ASIA-97, Seoul Hilton, Seoul, rep. Korea (May, 1997) staticdynamic Case of EVR – alpha,// in the case of ER-alpha || alpha-alpha both matrixes are static If there will follow an event under interest in the beam Off pause in the same strip, it will be pause prolongation up to min automatically Real PIPS detector (12 strip)  Image in PC 

Plus one explanation schematics Flowchart of the processPrinciple of background suppression * * B.N.Gikal: private communication

Statistical significance of the event ( main part ) One of the key questions of a rare event detecting procedure is a probability of the candidate to the real event to be a random In principle there are two basic approaches: LDSC ( K.-H. Schmidt et al., Z.Phys. A 316 (1984)19 ) and BSC (V.B. Zlokazov, Yad.Fiz. V.66, №9 (2003)1714)..others.. Can be easily represent according to the basis these concepts LDSC – formalize the concept of a L inked D ecay S ignal C ombination sequence analyzed does fit in this concept or not. ( in brief: a-priori info “Yes”) // key term – link between signals or between “starter” signal and following signal, depending on the scenario BSC – formalize the concept of Background Signal Combination and test, whether the signal sequence analyzed does fit the concept or not (a-priori info “No”) // key term – time interval between “start” and “finish”

LDSC, BSC (mnemonics) K-H. Schmidt, LDSC V.B. Zlokazov, BSC

K.-H. Schmidt mnemonics ( graphs ) Fixed Order  Partially free  Order timetime EVREVR SFSF a(i) time EVR SF SpontaneousFission  Flexible order (Yu.Tsyganov, JINR comm. P ) Alpha-decays In the manner, similar to K.-H. Schmidt : T – effective time T=n pixels T (exp), M signals are attributed to “unknown” nuclides and N-M-2 – to “known”. N- total number, including one SF. N SF -total fission fragment Number, λ-appropriate rates of event per coordinate pixel. Or, in simplified form:

Active correlation method ( EVR-α break points ) Graph for this case will be as shown in the figure: Small dead time ~10 Small dead time ~10 2 μs

LDSC philosophy frame for active correlation method (approach similar to BSC is in my paper Phys. Of Part. & Nucl. Lett. Vol.6 (2009) ) Being considering in the described above process a definite order correlated pair recoil-alpha E1  E2 as a starter signal Ê1  (E1  E2) for forthcoming sequences of “  ”-decays and following to the philosophy of [6] one can rewrite the equation (1) for the given case in the form of: Here the parameter denotes not any single signal rate per pixel, but a rate of correlations/pauses generating by the detection system during a long term experiment. Therefore, if N STOP is a total number of pauses measured in an experiment, to a first approximation :   Simplifications (only alpha decays, &λ i Δt i << 1) a mean counting rate value for alpha – decay signals measured in beam-OFF pauses by the focal plane detector. More common case of “starter” correlation signal Note, that N stop is a value measured in experiment!!!

Practical examples from SHE experiments… “advantage factor” (def) ξ = n b ( KHS )/n b ( present report), That is : (see also Yu.Tsyganov JINR P , p.6) Example #1, Z=113 from the reaction 273 Np+ 48 Ca  n; [Yu.Oganessian et al. PRC v.76 (2007)011601® ]. t 1 =0 (EVR), t 2 = s, t 3 = s, t 4 = s, t 5 = , t 6 =1993 s (SF).  ξ= / ≈ factor of 20 and n b ≤ 5∙ (except of ~ in the original paper) Example#2 Z=118 from the reaction 249 Cf+ 48 Ca  n; [ Yu.Oganessian et al. PRC v.74(2006)p ]. t1 = 0 (EVR), t2= , t3= , t4 = SF).  ξ≈ 2

Supplement #1 ( math. vs phys., general phylosophy // in the form of hyposthesis ) Idealization n b << 1 Real case f (n b / p CONFIG )=ń b ń b << 1 The simplest way ~ n b /p conf

examples Example #1 EVR – α – SF short chains (N=6, geom. Eff. For α – about 85%, second nuclide branch to SF ~ 50%. Combination N α =0 (real SHE experiments) ). One event has n b ~0.3. Having considering combination probability P(6, 0) – zero non-completed chains from six attempts, t.i. For our case p= 0.5*0.85=0.425, x( number of full event)=0, n=6. Example #2 Registration of one multi chain event like EVR-α-α-α-SF (see. Yu. Oganessian et al., Revista Mexicana de Fisica 46 Suplemento 1 (2000)35 ) All three alpha are with y-position and have full energy. Probability of this fact is p ~ (0.67) 3 ≈0.3. P(1,1) = p 1 ∙(1-p) 0 =0.3 ( additionally, one can take into account that efficiency to detect both fragments is not 100%, but around 40% !) V.B.Zlokazov Yad. Phys. V.66 N9 (2003) N m ~ (one pixel) => n b ~200 N m =0.08 So, ń b ~0.08/0.3 ≈0.3 (large enough!) => It’s difficult to say anything definite!!! (event or not event =to be or not to be!)  ń b =0.3/0.036 >>1 ! and this event should be excluded from the list

SUMMARY ( only two conclusions can be drawn here ) 1) Modification of LDSC method to estimate statistical significance of the multi-chain event measured with a position sensitive PIPS detector has been performed for the method of “active correlations” (case EVR-alpha ) 2) As a reasonable scenario, it is proposed to use some additional knowledge about event property (a priori +a posteriori..etc) to compare any calculated (LDSC or BSC…) statistic parameter with the real probability of the measured configuration of the candidate // in the form of hypothesis Yu.S.TsyganovNEC’2009 Sept. 08, Varna In memory of S.Iliev One of the best electronics engineer in the field of super heavy elements research