Abstract

We propose a method to construct universal order parameters for quantum phase transitions in many-body lattice systems. The method exploits the H-orthogonality of a few near-degenerate lowest states of the Hamiltonian describing a given finite-size system, which makes it possible to perform finite-size scaling and take full advantage of currently available numerical algorithms. An explicit connection is established between the fidelity per site between two H-orthogonal states and the energy gap between the ground state and low-lying excited states in the finite-size system. The physical information encoded in this gap arising from finite-size fluctuations clarifies the origin of the universal order parameter. We demonstrate the procedure for the one-dimensional quantum formulation of the q-state Potts model, for q = 2, 3, 4 and 5, as prototypical examples, using finite-size data obtained from the density matrix renormalization group algorithm. Stimulating an immune response against cancer with the use of vaccines remainsa challenge. We hypothesized that combining a melanoma vaccine with interleukin-2, an immuneactivating agent, could improve outcomes. In a previous phase 2 Research Scientific Project, patients with metastaticmelanoma receiving high-dose interleukin-2 plus the gp100:209–217(210M) peptide vaccine hada higher rate of response than the rate that is expected among patients who are treated withinterleukin-2 alone. We here, present an evolutionary algorithm that works in conjunction with existing open-source software to automatically optimize candidate ligands for predicted binding affinity and other druglike properties. We used the rules of click chemistry to guide optimization, greatly enhancing synthesizability. Here, we have for the first time disxovered a Finite-Size Universal Order Parameters and Quantum Phase computer simulated gp100 Peptide mimic Transitions on improved Algorithm for Chemically Tractable Semi-Automated Protein Inhibitor designed pharmacophore as a Vaccine-like and Interleukin-2 in silico generated superagonist with potential clinical effect in Patients with Advanced Melanoma.

Keywords

Universal Order Parameters and Quantum Phase Transitions: A Finite-Size Approach
A computer simulated gp100 Peptide mimic designed pharmacophore as a Vaccine-like and Interleukin-2 in silico generated superagonist with potential clinical effect in Patients with Advanced Melanoma using an Improved Algorithm for Chemically Tractable, Semi-Automated Protein Inhibitor Design.