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Hello Peter,
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<div class="">Thanks a lot for your email. I find your project very interesting and inspiring and I’d be delighted to find a way to collaborate.</div>
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<div class="">See below the answers to some of your comments:</div>
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<blockquote type="cite" class="">The Cryptech RNG is implemented in an FPGA, so many digital<br class="">
interfaces are theoretically possible.<br class="">
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What low level interface(s) does your QRNG use? The whitepaper you<br class="">
linked only mentions high level interfaces such as PCIe and Ethernet,<br class="">
which may not be so suitable because of relatively high complexity.<br class="">
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<div>Our entropy source (ES) is also controlled by an FPGA now. We can adapt interfacing issues to adapt to the needs of your solution. Currently, the format of the random bits is a parallel 8-bit LVDS signal, and we need some extra signals to control the ES.
All of them can be generated from an FPGA.</div>
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<blockquote type="cite" class="">The whitepaper says "multi gigabit per second bit rate." on page 4<br class="">
but nothing more specific.<br class="">
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<div>The final bitrate we can provide depends on the target price. Our optical system has been proven up to 42 Gb/s, but then the electronics, ADC and processing gets very expensive. What do you think would be an attractive RNG bitrate for your HSMs?</div>
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<blockquote type="cite" class="">nor results form tests using tools like Ent, Diheharder not NIST<br class="">
tests in SP 800-22, all commonly used to test entropy sources and<br class="">
random generators.<br class="">
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Right, it would be good to run those tests for a while, maybe ICFO<br class="">
have so far focused on the histogram in Figure 2.<br class="">
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<div>Our approach is to test the predictability (or extractable entropy) using experimental measures only, not statistical measures or tests. These methods are very ineffective to test randomness. Our methodology (which shares similarities with latest standardisation
efforts for RNGs) was presented in Phys. Rev. A, 91, 012314 (2015) [you can find an open source version of the manuscript here <a href="https://arxiv.org/abs/1506.02712" class="">https://arxiv.org/abs/1506.02712</a>]. We applied this methodology to the RNGs
we developed for last year loophole-free Bell test experiments published in Nature. You can find all the characterisation in our Phys. Rev. Lett. (2016) publication [an open-source version can be found in <a href="https://arxiv.org/pdf/1506.02712v2.pdf" class="">https://arxiv.org/pdf/1506.02712v2.pdf</a>].
At the end of this document, you can see the results of some statistical tests that we used as health monitors (more than 1 Tb of data was tested). Mostly, we use the Alphabit battery of the TestU01 suite, which was specifically designed for testing physical
RNGs.</div>
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<div>Best,</div>
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<div>Carlos</div>
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//Peter<br class="">
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