<?xml version="1.0" encoding="UTF-8" ?>
<rss version="2.0">
    <channel>
      <title>Christopher K. Long</title>
      <link>https://Christopher-K-Long.ac</link>
      <description>Last 10 notes on Christopher K. Long</description>
      <generator>Quartz -- quartz.jzhao.xyz</generator>
      <item>
    <title>About</title>
    <link>https://Christopher-K-Long.ac/About</link>
    <guid>https://Christopher-K-Long.ac/About</guid>
    <description><![CDATA[ The purpose of this website is to collate my works and ideas in an independent, open, and future-proof manner. This page outlines each of these design philosophies. ]]></description>
    <pubDate>Tue, 06 Oct 2026 15:52:02 GMT</pubDate>
  </item><item>
    <title>Almost sure minimality of the set of experiments with classical Kirkwood-Dirac representations</title>
    <link>https://Christopher-K-Long.ac/Articles/Almost-sure-minimality-of-the-set-of-experiments-with-classical-Kirkwood-Dirac-representations</link>
    <guid>https://Christopher-K-Long.ac/Articles/Almost-sure-minimality-of-the-set-of-experiments-with-classical-Kirkwood-Dirac-representations</guid>
    <description><![CDATA[ We show that if two d-dimensional observables are picked at random, the set of classical states of the resulting KD distribution is a minimal polytope of dimension 2(d−1). ]]></description>
    <pubDate>Tue, 06 Oct 2026 15:52:02 GMT</pubDate>
  </item><item>
    <title>Dynamic adaptive quantum approximate optimization algorithm for shallow, noise-resilient circuits</title>
    <link>https://Christopher-K-Long.ac/Articles/Dynamic-adaptive-quantum-approximate-optimization-algorithm-for-shallow,-noise-resilient-circuits</link>
    <guid>https://Christopher-K-Long.ac/Articles/Dynamic-adaptive-quantum-approximate-optimization-algorithm-for-shallow,-noise-resilient-circuits</guid>
    <description><![CDATA[ We present the dynamic adaptive quantum approximate optimization algorithm (Dynamic-ADAPT-QAOA). Our algorithm significantly reduces the circuit depth and the CNOT count of standard ADAPT-QAOA. ]]></description>
    <pubDate>Tue, 06 Oct 2026 15:52:02 GMT</pubDate>
  </item><item>
    <title>From virtual Z gates to virtual Z pulses</title>
    <link>https://Christopher-K-Long.ac/Articles/From-virtual-Z-gates-to-virtual-Z-pulses</link>
    <guid>https://Christopher-K-Long.ac/Articles/From-virtual-Z-gates-to-virtual-Z-pulses</guid>
    <description><![CDATA[ We develop a theory of virtual Z rotations at the Hamiltonian level. This allows Z terms to be added to the Hamiltonian at no additional cost. ]]></description>
    <pubDate>Tue, 06 Oct 2026 15:52:02 GMT</pubDate>
  </item><item>
    <title>Hardware-tailored resource estimation for magic-state distillation on silicon spin qubits</title>
    <link>https://Christopher-K-Long.ac/Articles/Hardware-tailored-resource-estimation-for-magic-state-distillation-on-silicon-spin-qubits</link>
    <guid>https://Christopher-K-Long.ac/Articles/Hardware-tailored-resource-estimation-for-magic-state-distillation-on-silicon-spin-qubits</guid>
    <description><![CDATA[ We present a resource analysis for generating high-fidelity logical magic states on silicon spin-qubit platforms. ]]></description>
    <pubDate>Tue, 06 Oct 2026 15:52:02 GMT</pubDate>
  </item><item>
    <title>Layering and subpool exploration for adaptive variational quantum eigensolvers: Reducing circuit depth, runtime, and susceptibility to noise</title>
    <link>https://Christopher-K-Long.ac/Articles/Layering-and-subpool-exploration-for-adaptive-variational-quantum-eigensolvers:-Reducing-circuit-depth,-runtime,-and-susceptibility-to-noise</link>
    <guid>https://Christopher-K-Long.ac/Articles/Layering-and-subpool-exploration-for-adaptive-variational-quantum-eigensolvers:-Reducing-circuit-depth,-runtime,-and-susceptibility-to-noise</guid>
    <description><![CDATA[ We provide a framework for producing shallow ADAPT-VQE circuits and analyse their robustness to noise. ]]></description>
    <pubDate>Tue, 06 Oct 2026 15:52:02 GMT</pubDate>
  </item><item>
    <title>Minimal state-preparation times for silicon spin qubits</title>
    <link>https://Christopher-K-Long.ac/Articles/Minimal-state-preparation-times-for-silicon-spin-qubits</link>
    <guid>https://Christopher-K-Long.ac/Articles/Minimal-state-preparation-times-for-silicon-spin-qubits</guid>
    <description><![CDATA[ We numerically estimate the minimum evolution time for a range of state-preparation tasks on silicon spin-qubit quantum processors. ]]></description>
    <pubDate>Tue, 06 Oct 2026 15:52:02 GMT</pubDate>
  </item><item>
    <title>PhD thesis: &quot;Optimal Hamiltonian control for variational quantum algorithms: On spin-qubit quantum processors&quot;</title>
    <link>https://Christopher-K-Long.ac/Articles/PhD-thesis</link>
    <guid>https://Christopher-K-Long.ac/Articles/PhD-thesis</guid>
    <description><![CDATA[ Christopher K. Long Supervisors: Crispin H. W. Barnes, Frederico Martins, David R. M. Arvidsson-Shukur, and Normann Mertig Examiners: Alex J. W. ]]></description>
    <pubDate>Tue, 06 Oct 2026 15:52:02 GMT</pubDate>
  </item><item>
    <title>Pulse-optimised circuit elements for scalable and noise-resilient quantum chemistry</title>
    <link>https://Christopher-K-Long.ac/Articles/Pulse-optimised-circuit-elements-for-scalable-and-noise-resilient-quantum-chemistry</link>
    <guid>https://Christopher-K-Long.ac/Articles/Pulse-optimised-circuit-elements-for-scalable-and-noise-resilient-quantum-chemistry</guid>
    <description><![CDATA[ Using quantum optimal control, we engineer parameterized two- and four-qubit gates for quantum chemistry tasks. ]]></description>
    <pubDate>Tue, 06 Oct 2026 15:52:02 GMT</pubDate>
  </item><item>
    <title>Quantifying the advantages of applying quantum approximate algorithms to portfolio optimisation</title>
    <link>https://Christopher-K-Long.ac/Articles/Quantifying-the-advantages-of-applying-quantum-approximate-algorithms-to-portfolio-optimisation</link>
    <guid>https://Christopher-K-Long.ac/Articles/Quantifying-the-advantages-of-applying-quantum-approximate-algorithms-to-portfolio-optimisation</guid>
    <description><![CDATA[ We present a quantum algorithm for portfolio optimization. Specifically, we present an end-to-end quantum approximate optimization algorithm to solve the discrete global minimum variance portfolio model. ]]></description>
    <pubDate>Tue, 06 Oct 2026 15:52:02 GMT</pubDate>
  </item>
    </channel>
  </rss>