Zero-knowledge universal lossless data compression

Advanced instrumentation, dealing with nanoscale technology at the current edge of human scientific enquiry, like X-Ray CT, generates an enormous quantity of data from single experiment. The very best modern lossless data compression algorithms use standard approaches and are unable to match high end requirements for mission critical application with full information conservation (a few pixels may vary by com/decom processing). In previous papers published elsewhere, we have already shown that traditional Q Arithmetic can be regarded as a highly sophisticated open logic, powerful and flexible bidirectional formal language of languages, according to “Computational Information Conservation Theory” (CICT). This new awareness can offer competitive approach to guide more convenient algorithm development and application for combinatorial lossless compression. To achieve true lossless com/decom and to overcome traditional constraints, the universal modular arithmetic approach, based on CICT Solid Number (SN) concept, is presented. To check practical implementation performance and effectiveness, an example on computational imaging is benchmarked by key performance index and compared to standard well-known lossless compression techniques. Results are critically discussed.