<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/9B3BF655-5ED9-40F3-BB65-1AD920A4334D" ns1:id="9B3BF655-5ED9-40F3-BB65-1AD920A4334D"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/7A32DEE4-BEB5-45A0-B01B-3E41F329FCB3" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/3D25D026-1CFC-406E-AF89-23C5190F7192" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/1875ACF9-9A99-40BC-849F-2E7467DACD7E" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/3D25D026-1CFC-406E-AF89-23C5190F7192" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/9D2EB31E-E965-49ED-A49A-E95FFD22D861" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2024-02-29T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/D3C1B92C-F408-49AC-B6FC-AD1E177C6CB2" ns1:rel="FUND" ns1:start="2022-12-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10031836</ns2:identifier></ns2:identifiers><ns2:title>High-speed self-certifying Quantum Random Number Generator for simulations</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>ISCF</ns2:leadFunder><ns2:abstractText>Random number generators (RNGs) are used for a myriad of different applications, ranging from encryption to non-cryptographic use cases such as stochastic simulations. However, the quality of RNGs is often overlooked but can significantly improve the accuracy and time to solution of stochastic modelling methodologies in addition to the effectiveness of encryption schemes. Quantum Random Number Generators (QRNGs) improve on the commonplace pseudo- and quasi-random generators due to the intrinsically unpredictable nature of quantum physical processes. We will combine a QRNG from Quantum Dice with the Hartree Centre's Monte Carlo capabilities and demonstrate their usage on test cases relevant to the Financial Services sector under the guidance of HSBC.</ns2:abstractText></ns2:project>