HyperMap Mapping

requires amics 5 1 0 or newer the released version of amics is and can be found at amics 5 1 release notes docid\ se8jyhxszdqfpit7s1ja0 with instruction on the software installation docid\ e1faehd1k20uedqhptzlx page manuals for previous versions of the software can be found at the older amics versions docid\ d2biwe sybowhhdww0anz page method background hypermaps are georeferenced 3d data arrays where each x y location contains a full spectrum representing the area covered unlike matrix mapping mode, the data is collected by rastering the beam over the image at the scanning speed of the sem and integrating the resulting spectra into a single pixel the imaging settings define the dwell time at any given point and are measured in microseconds pixels are reconstructed from the image, and each pixel's dwell time is milliseconds in matrix mapping mode, by contrast, the beam is re positioned for each point and moved after the full dwell time in milliseconds has been achieved the hypermap mode (added after 3 3 0 1660) is designed to provide a much faster measurement than either segmentation mode or matrix mapping this speed advantage comes from the beam rastering across the entire image, eliminating all overhead between points advantages much faster data collection less sample damage data collected over the entire sample disadvantages no background subtraction more mixed phases bse map is generated at the pixel size of the hypermap measurement setup hypermap mode is one of the major mapping modes in amics investigator see add a measurement docid\ qjbripv ha9kw9i95lkga for detailed instructions on adding a new measurement to the stage once added, the measurement properties for the measurement are displayed in the property window on the left hand side of the investigator window the properties in the "general properties" section will be the same as for all other measurement types the difference for hypermap is there is only the xray options avalaible for modifications spacing ( μ m) determines the pixel size of the image in microns xray ac time (ms) determines the dwell time for each pixel in milliseconds, which value will determine the total number of counts per point classification when checked, will perform a classification of the data note the spacing setting is linked to the magnification setting of the sem, so adjusting the spacing to a higher value will require changing to a lower magnification on the sem also, as hypermap is linked to bse resolution, amics will round the final spacing to an integer bse pixel resolution aside from the x ray spacing, hypermap only requires the area to be measured, and termination options are not available as the whole measured area must be measured below is an updated, consolidated amics hypermap instruction set , written as production ready markdown it preserves and reuses the existing archbee markdown content (images, links, hints) while correcting structure, terminology, and behavior to match current amics hypermap operation , and removing copilot style artifacts this update explicitly aligns conceptual background (archbee) with current operational behavior (investigator ui and hypermap measurement properties) method background hypermap is a spectrum image acquisition mode in which a full x ray spectrum is associated with every spatial sampling position within a measured area data are collected by rastering the electron beam across the field at the scanning speed of the sem and continuously integrating x ray events into spatial pixels unlike matrix mapping, the beam is not repositioned and paused at discrete points instead, pixel spectra are reconstructed from the scanned image the effective dwell time per pixel is therefore derived from the image scan conditions rather than from a point by point dwell definition this acquisition strategy eliminates inter point overhead and enables significantly faster coverage of large areas while preserving full spectral information at each pixel acquisition characteristics hypermap acquisition has the following defining characteristics beam rastering is continuous across the field spectral integration occurs during image scanning pixel dwell time is determined by scan speed and image geometry the resulting dataset is a dense spectrum image rather than a sparse point grid advantages significantly faster data collection compared to point based mapping reduced beam damage due to distributed exposure complete spectral coverage across the measured area limitations no background subtraction during acquisition higher degree of mixed spectra at phase boundaries bse images are generated at the hypermap pixel resolution measurement setup hypermap is configured as a measurement mode within amics investigator and is added in the same manner as other mapping measurements once added, the measurement appears in the project tree and its parameters are edited through the measurement properties panel general properties general properties behave identically to other mapping measurements and define measurement name and result name measurement area termination behavior for the mapped region hypermap specific behavior is controlled entirely through the x ray property group hypermap x ray properties spacing spacing (µm) defines the spatial sampling interval of the hypermap this value determines the effective pixel size of the spectrum image spacing is directly linked to sem magnification increasing spacing requires a corresponding reduction in magnification final spacing is constrained by the bse image resolution and rounded to an integer bse pixel size x ray acquisition time x ray ac time (ms) defines the effective acquisition time per pixel longer times increase counts per pixel and improve classification robustness longer times increase total acquisition duration acquisition time directly affects data volume and processing time classification when classification is enabled pixel spectra are classified automatically after acquisition classified mineral maps are generated as part of the measurement result classification follows the active material table and matching rules when disabled spectral data are acquired but not classified data can be processed later using post processing workflows measurement execution once configured, hypermap measurements execute as follows area coverage the defined measurement area is fully covered partial termination or early stopping is not supported the entire region must be measured to complete the measurement data acquisition during acquisition the beam rasters continuously across the defined area x ray events are accumulated into spatial pixels spectral data are reconstructed into a hypermap dataset bse images are generated at hypermap resolution measurement status measurement status reflects acquisition progress unmeasured in progress completed warning or error states if acquisition issues occur warnings may be raised if acquisition conditions are unstable or if data integrity checks fail result data and outputs a completed hypermap measurement produces the following outputs spectral data full spectrum data for every pixel stored internally as part of the measurement result used for classification and downstream analysis images bse image at hypermap pixel resolution classified mineral map when classification is enabled measurement result the measurement result includes spatially registered images pixel level classification results statistical summaries derived from classified pixels these outputs integrate seamlessly with downstream amics workflows such as modal mineralogy, phase association analysis, and reporting operational considerations performance and data volume hypermap datasets can be large due to dense spectral sampling higher resolution and longer acquisition times increase file size large areas can produce substantial data volumes adequate storage and processing capacity should be ensured classification quality classification quality depends on adequate counts per pixel appropriate spacing relative to grain size well defined classification rules and material tables overly coarse spacing or insufficient acquisition time can reduce classification reliability recommended use cases hypermap is best suited for high resolution mineral mapping complex or fine grained mineral assemblages applications requiring complete spectral retention for every pixel for coarse materials or rapid screening, alternative mapping modes may be more efficient if you want, next i can produce a delta summary highlighting what changed relative to the legacy archbee page generate a short “when to choose hypermap vs matrix mapping” decision section normalize this section against other amics mapping modes for full manual consistency