arXiv subjects

Mark A. Novotny

Publications and source records attributed to Mark A. Novotny.

9 recordsLinked to original sources

arXiv2026

Degeneracy Counting Quantum Algorithm using Decoherence

Counting the global optima of a classical optimization problem is a #P-hard task. We develop the canonical thermal pure quantum (CTPQ) state-based degeneracy counting (CTPQsd#) algorithm that determines the number of global optima of a classical optimization problem P by measuring only a small probe S, without finding individual minima. The method exploits a perturbative relation between the decoherence measure of S and the degeneracy of P when S and P are together in a CTPQ state. We provide the first numerical demonstration that this relation can be used to count the global minima, applying it to problems encoded by diagonal random-energy Hamiltonians as a maximally unstructured testbed for classical binary optimization problems. Classical simulations of up to 20 problem qubits quantify the algorithm's sensitivity to variations in the temperature of the CTPQ state, the Hamiltonian energy range, the problem size, and degeneracy. We establish the temperature threshold for determining the exact degeneracy and identify a second, lower threshold that provides a temperature window to count near-degenerate minima within a user-defined energy tolerance. By confining measurement to S, the protocol replaces tomography over the exponentially large problem Hilbert space with tomography over a small probe represented by only four qubits.

cs.LG↗

arXiv2026

Training Quantum Dragons

The Non-Equilibrium Green's Function (NEGF) is the standard formalism for nano-scale electron transport. By recasting the NEGF scattering problem as a linear system of equations whose solution encodes the transmission and reflection amplitudes, we present the first quantum computerized implementation of NEGF. We apply both the Harrow--Hassidim--Lloyd and Variational Quantum Linear Solver algorithms to compute the transmission coefficient $T(E)$ of quantum dragon nanodevices within the single-band tight-binding model. Quantum dragon devices exhibit perfect transmission across the full conducting band regardless of internal disorder. The problem maps onto compact circuits of 3 and 4 total physical qubits for the 2-site and 6-site dragon devices, respectively. A similarity transformation block-diagonalizes the NEGF linear system reducing the Pauli decomposition of the block-encoded matrix. We demonstrate the feasibility of quantum computation by performing ideal and noise-aware simulations and computations on physical IBM quantum processor.

quant-ph↗

arXiv2026

Assembly to Quantum Compiler

This research presents a novel approach in quantum computing by transforming ARM assembly instructions for use in quantum algorithms. The core achievement is the development of a method to directly map the ARM assembly language, a staple in classical computing, to quantum computing paradigms. The practical application of this methodology is demonstrated through the computation of the Fibonacci sequence. This example serves to validate the approach and underscores its potential in simplifying quantum algorithms. Grover's Algorithm was realized through the use of quantum-specific instructions. These transformations were developed as part of an open-source assembly-to-quantum compiler (github.com/arhaverly/AssemblyToQuantumCompiler). This effort introduces a novel approach to utilizing classical instruction sets in quantum computing and offers insight into potential future developments in the field. The AssemblyToQuantumCompiler streamlines quantum programming and enables computer scientists to transition more easily from classical to quantum computer programming.

quant-ph↗

arXiv2021

Training a quantum annealing based restricted Boltzmann machine on cybersecurity data

We present a real-world application that uses a quantum computer. Specifically, we train a RBM using QA for cybersecurity applications. The D-Wave 2000Q has been used to implement QA. RBMs are trained on the ISCX data, which is a benchmark dataset for cybersecurity. For comparison, RBMs are also trained using CD. CD is a commonly used method for RBM training. Our analysis of the ISCX data shows that the dataset is imbalanced. We present two different schemes to balance the training dataset before feeding it to a classifier. The first scheme is based on the undersampling of benign instances. The imbalanced training dataset is divided into five sub-datasets that are trained separately. A majority voting is then performed to get the result. Our results show the majority vote increases the classification accuracy up from 90.24% to 95.68%, in the case of CD. For the case of QA, the classification accuracy increases from 74.14% to 80.04%. In the second scheme, a RBM is used to generate synthetic data to balance the training dataset. We show that both QA and CD-trained RBM can be used to generate useful synthetic data. Balanced training data is used to evaluate several classifiers. Among the classifiers investigated, K-Nearest Neighbor (KNN) and Neural Network (NN) perform better than other classifiers. They both show an accuracy of 93%. Our results show a proof-of-concept that a QA-based RBM can be trained on a 64-bit binary dataset. The illustrative example suggests the possibility to migrate many practical classification problems to QA-based techniques. Further, we show that synthetic data generated from a RBM can be used to balance the original dataset.

quant-ph↗

arXiv2007

EC-FORC: A New Cyclic Voltammetry Based Method for Examining Phase Transitions and Predicting Equilibrium

We propose a new, cyclic-voltammetry based experimental technique that can not only differentiate between discontinuous and continuous phase transitions in an adsorbate layer, but also quite accurately recover equilibrium behavior from dynamic analysis of systems with a continuous phase transition. The Electrochemical first-order reversal curve (EC-FORC) diagram for a discontinuous phase transition (nucleation and growth), such as occurs in underpotential deposition, is characterized by a negative region, while such a region does not exist for a continuous phase transition, such as occurs in the electrosorption of Br on Ag(100). Moreover, for systems with a continuous phase transition, the minima of the individual EC-FORCs trace the equilibrium curve, even at very high scan rates. Since obtaining experimental data for the EC-FORC method would require only a simple reprogramming of the potentiostat used in conventional cyclic-voltammetry experiments, we believe that this method has significant potential for easy, rapid, in-situ analysis of systems undergoing electrochemical deposition.

physics.chem-ph↗

arXiv2002

Low-temperature Metastability of Ising Models: Prefactors, Divergences, and Discontinuities

The metastable lifetime of the square-lattice and simple-cubic-lattice kinetic Ising models are studied in the low-temperature limit. The simulations are performed using Monte Carlo with Absorbing Markov Chain algorithms to simulate extremely long low-temperature lifetimes. The question being addressed is at what temperatures the mathematically rigorous low-temperature results become valid. It is shown that the answer depends partly on how close the system is to fields at which the prefactor for the metastable decay either has a discontinuity or diverges.

cond-mat.stat-mech↗

arXiv1999

Introduction to the Propp-Wilson Method of Exact Sampling for the Ising Model

An introduction to the Propp-Wilson method of coupling-from-the-past for the Ising model is presented. It enables one to obtain exact samples from the equilibrium spin distribution for ferromagnetic interactions. Both uniform and random quenched magnetic fields are included. The time to couple from the past and its standard deviation are shown as functions of system size, temperature, and the field strength. The time should be an estimate of the ergodic time for the Ising system.

cond-mat.mtrl-sci↗

arXiv1995

Analytical and computational study of magnetization switching in kinetic Ising systems with demagnetizing fields

An important aspect of real ferromagnetic particles is the demagnetizing field resulting from magnetostatic dipole-dipole interaction, which causes large particles to break up into domains. Sufficiently small particles, however, remain single-domain in equilibrium. This makes such small particles of particular interest as materials for high-density magnetic recording media. In this paper we use analytic arguments and Monte Carlo simulations to study the effect of the demagnetizing field on the dynamics of magnetization switching in two-dimensional, single-domain, kinetic Ising systems. For systems in the ``Stochastic Region,'' where magnetization switching is on average effected by the nucleation and growth of fewer than two well-defined critical droplets, the simulation results can be explained by the dynamics of a simple model in which the free energy is a function only of magnetization. In the ``Multi-Droplet Region,'' a generalization of Avrami's Law involving a magnetization-dependent effective magnetic field gives good agreement with our simulations.

cond-mat↗

arXiv1995

Kinetic Ising Systems as Models of Magnetization Switching in Submicron Ferromagnets

Recently experimental techniques, such as magnetic force microscopy (MFM), have enabled the magnetic state of individual sub-micron particles to be resolved. Motivated by these experimental developments, we use Monte Carlo simulations of two-dimensional kinetic Ising ferromagnets to study the magnetic relaxation in a negative applied field of a grain with an initial magnetization $m_0 = +1$. The magnetostatic dipole-dipole interactions are treated to lowest order by adding to the Hamiltonian a term proportional to the square of the magnetization. We use droplet theory to predict the functional forms for some quantities observed by MFM, such as the probability that the magnetization is positive. Our simulations are in excellent agreement with droplet-theoretical predictions. The qualitative agreement between experiments and our simulations of switching in individual single-domain ferromagnets indicates that the switching mechanism in such particles may involve local nucleation and subsequent growth of droplets of the stable phase.

cond-mat↗