Device and method for responding to influences of mind

• US 8,073,631 B2
• Filed: 07/21/2006
• Issued: 12/06/2011
• Est. Priority Date: 07/22/2005
• Status: Expired

• Current Assignee: Psigenics Corporation
• Original Assignee: Psigenics Corporation
• Inventors: Wilber, Scott A., Wilber, Patrick A., Jensen, Christopher B.
• Primary Examiner(s): TSAI, CAROL S W
• Application Number:
  US11/989,078
• Publication Number:
  US 20090265112A1
• Time in Patent Office: 1,964 Days
• Field of Search: 702/19, 702/186, 708/250, 708/251, 708/253, 708/255, 341/131, 331/46, 331/47, 331/78
• US Class Current: 702/19
• CPC Class Codes: B82Y 10/00 Nanotechnology for information processing, storage or transmission, e.g. quantum computing or single electron logic
• CPC Class Codes: G06F 7/588 Random number generators, i.e. based on natural stochastic processes
• CPC Class Codes: G06N 10/00 Quantum computing, i.e. information processing based on quantum-mechanical phenomena

Abstract

In the field of direct mind-machine interactions, prior art devices and methods do not provide sufficiently fast and reliable results. Mental influence detectors (100, 140, 400, 430) and corresponding methods provide fast and reliable results useful for detecting an influence of mind and hidden or classically non-inferable information. An anomalous effect detector (100) includes a source (104) of non-deterministic random numbers (110), a converter (114) to convert a property of numbers, a processor to accept converter output (118) and to produce an output signal (124) representative of an influence of mind. The processor output signal (124) contains fewer numbers than the input (110). A quantum computer (400) includes a physical source of entropy (404) to generate output numbers (405); a source (406) of test numbers (407); a measurement processor 410) to accept output numbers (405) and to measure a relationship between process numbers and at least one test number to produce an output (414) representative of an influence of mind.

Claims

1. A method of detecting an influence of mind, comprising:

providing input numbers from a source of non-deterministic random numbers;

converting a property of said input numbers into a converter output comprising bias representative of said property, wherein said converting comprises amplifying bias in a bias amplifier, and wherein bias is expressed as the fraction of ones to total bits in a sequence of binary numbers;

producing a processor output signal representative of an influence of mind by processing said converter output, wherein said processor output signal contains fewer numbers than said input numbers; and

communicating said processor output signal.

2. A method of detecting an influence of mind as in claim 1 wherein said providing said input numbers comprises:

reducing a statistical defect in said input numbers.

3. A method of detecting an influence of mind as in claim 2 wherein:

said reducing a statistical defect reduces bias in said input numbers to less than 10 ppm and reduces autocorrelation in said input numbers to less than 10 ppm.

4. A method of detecting an influence of mind as in claim 1 wherein said providing input numbers comprises:

generating input numbers having a bias less than 10 ppm and an autocorrelation less than 10 ppm.

5. A method of detecting an influence of mind as in claim 1 wherein:

said converting a property of said input numbers comprises at least one step of converting selected from the group consisting of;

converting a cross-correlation to a bias representative of said cross-correlation, converting a mutual bias to a bias representative of said mutual bias, and converting runs to a bias representative of said runs.

6. A method of detecting an influence of mind as in claim 1 wherein said amplifying a bias comprises:

performing a truth table bias function.

7. A method of detecting an influence of mind as in claim 1 wherein said amplifying a bias comprises:

performing a bounded random walk.

8. A method of detecting an influence of mind as in claim 1 wherein said converting a property of said input numbers comprises:

converting autocorrelation in said input numbers into a bias representative of said autocorrelation.

9. A method of detecting an influence of mind as in claim 1, further comprising:

providing at least one test number;

measuring a relationship between said converter output and said at least one test number to produce a relationship measurement; and

abstracting said relationship measurement to provide an enhanced output signal representative of said influence of mind.

10. A method of detecting an influence of mind as in claim 9 wherein said providing said at least one test number comprises:

providing test numbers having a fixed pattern.

11. A method of detecting an influence of mind as in claim 9, further comprising:

initiating a detection of said influence of mind using an initiator; and

wherein said providing said at least one test number comprises providing at least one test number before said initiating said detection.

12. A method of detecting an influence of mind as in claim 9, further comprising:

initiating a detection of said influence of mind using an initiator;

wherein said providing said at least one test number comprises providing at least one test number after said converting a property of said input numbers into a converter output.

13. A method of detecting an influence of mind as in claim 1 wherein said providing said input numbers comprises:

providing input numbers from a source of non-deterministic random numbers located in a device selected from the group consisting of an FPGA and an ASIC.

14. A method of detecting an influence of mind as in claim 13 wherein said providing input numbers comprises:

using an independent ring oscillator.

15. A method of detecting an influence of mind as in claim 1, further comprising:

initiating a detection of said influence of mind.

16. A method of detecting an influence of mind as in claim 15 comprising:

receiving a conditioned physiological measurement to initiate a detection.

17. A method of detecting an influence of mind as in claim 15 comprising:

receiving an output from an influence-of-mind detector to initiate a detection.

18. A method of detecting an influence of mind as in claim 15 wherein said detection is initiated automatically and periodically.

19. A method of detecting an influence of mind as in claim 1 wherein said communicating said processor output signal comprises using an interface selected from the group consisting of:

a cell phone screen and a cell phone speaker.

20. A method of detecting an influence of mind as in claim 1 wherein said communicating said processor output signal comprises communicating using the internet.

21. A method of detecting an influence of mind as in claim 1 wherein said providing input numbers from a source of non-deterministic random numbers is performed spatially separated from said communicating said processor output signal.

22. An influence-of-mind detector, comprising:

a source of non-deterministic random numbers;

a converter operable to accept input numbers from said source and to convert a property of said input numbers into a converter output comprising amplified bias representative of said property, wherein bias is expressed as the fraction of ones to total bits in a sequence of binary numbers;

a bias amplifier included in said converter;

a processor that is operable to accept said converter output and to produce a processor output signal representative of an influence of mind;

wherein said processor output signal contains fewer numbers than said input numbers; and

an interface that is operable to communicate said processor output signal.

23. An influence-of-mind detector as in claim 22 wherein said source of non-deterministic random numbers comprises:

a randomness corrector.

24. An influence-of-mind detector as in claim 22 wherein said converter comprises:

an autocorrelation converter that is operable to convert autocorrelation in said input numbers into a bias that is representative of said autocorrelation.

25. An influence-of-mind detector as in claim 22, further comprising:

a source of test numbers; and

wherein

said processor is operable to measure a relationship between said converter output in said processor and at least one test number to produce a relationship measurement; and

said processor is further operable to abstract said relationship measurement to provide an enhanced output signal representative of said influence of mind.

26. An influence-of-mind detector as in claim 22 wherein said source of non-deterministic random numbers is located in a device selected from the group consisting of an FPGA and an ASIC.

27. An influence-of-mind detector as in claim 26 wherein said source of non-deterministic random numbers comprises:

an independent ring oscillator.

28. An influence-of-mind detector as in claim 22, further comprising;

an initiator that is operable to initiate a detection of an influence of mind.

29. An influence-of-mind detector as in claim 22 wherein said interface is selected from the group consisting of:

a cell phone screen and a cell phone speaker.

30. An influence-of-mind detector as in claim 22 wherein said interface comprises an internet-enabled device.

31. An influence-of-mind detector as in claim 22 wherein said source of non-deterministic random numbers is spatially separated from said interface.