Transient Space Charge Limited Picosecond Pulses Using Ultra Short Laser Pulses
Bibliographic record
Abstract
The generation of short and powerful electron bunches and electromagnetic pulses (EMP) is a major requirement for many applications such as ultrawide band (UWB) radar sensors [1] , generation of picosecond X-ray pulses, ultra-fast electron diffraction and microscopy and as pulsed high brightness picosecond electron guns for SEM. Here we investigate a technique to generate high voltage ultra-short pulses using vacuum photo diodes for application in UWB radar sensors. The maximum current flux which can be extracted is determined by the space charge limit [2] . Here we develop a self similar analytic model for calculating the peak current and duration of the space charge limited pulses for the case of ultrashort (on the order of a picosecond or less) laser excitation of a photocathode. In order to compare to a real physical system, the pulse widths are calculated for the case of a 3 mm diode gap with various potentials ranging from 1kV to 5kV applied to the anode. In order to verify the self similar analytic solutions derived, numerical modelling of the transient pulse generation was also carried out using a 1D non-relativistic electrostatic Particle in Cell (PIC) code. The results show the possibility of generating EMP pulses of 100 ps or less in duration with peak currents of several amps leading to voltage pulses of hundreds of volts into 50 ohm loads with photocathode areas of the order of 1 cm 2 . The possibility to generate such pulses using high repetition rate (order of 10 kHz - 1 MHz) laser systems will be discussed in detail.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".