arXiv subjects

Andrew Wright

Publications and source records attributed to Andrew Wright.

13 recordsLinked to original sources

arXiv2026

Double-bracket quantum algorithms for thermal state preparation

We propose quantum algorithms for preparing thermal states via the simulation of the thermofield double states. The key idea is to leverage double-bracket quantum algorithms to implement imaginary-time evolution on thermofield double states, whose reduced state realizes the Gibbs state. Our method, termed double-bracket thermofield double (DB-TFD), introduces two variants. The first, the vanilla DB-TFD algorithm, directly implements imaginary-time evolution using double-bracket quantum imaginary-time evolution. The second, poly DB-TFD, employs double-bracket quantum signal processing to approximate the imaginary-time evolution operator via a polynomial transformation. We demonstrate that the complexity of the poly DB-TFD algorithm scales exponentially with the inverse temperature in a broad practical regime. This scaling is consistent with existing methods, and numerical simulations support the corresponding theoretical bound. We further demonstrate the utility of DB-TFD in quantum Boltzmann machines for generative modeling, achieving improved performance compared with variational imaginary-time evolution approaches. These results establish DB-TFD as a promising route for thermal state preparation in the near-term and early-fault-tolerant regimes.

quant-ph↗

arXiv2026

Thermal State Simulation with Pauli and Majorana Propagation

We introduce a propagation-based approach to thermal state simulation by adapting Pauli and Majorana propagation to imaginary-time evolution in the Schr\"odinger picture. Our key observation is that high-temperature states can be sparse in the Pauli or Majorana bases, approaching the identity at infinite temperature. By formulating imaginary-time evolution directly in these operator bases and evolving from the maximally mixed state, we access a continuum of temperatures where the state remains efficiently representable. We provide analytic guarantees for small-coefficient truncation and Pauli-weight (Majorana-length) truncation strategies by quantifying the error growth and the impact of backflow. Large-scale numerics on the 1D J1-J2 model (energies) and the triangular-lattice Hubbard model (static correlations) validate efficiency at high temperatures.

quant-ph↗

arXiv2024

Strategies for optimizing double-bracket quantum algorithms

Recently double-bracket quantum algorithms have been proposed as a way to compile circuits for approximating eigenstates. Physically, they consist of appropriately composing evolutions under an input Hamiltonian together with diagonal evolutions. Here, we present strategies to optimize the choice of the double-bracket evolutions to enhance the diagonalization efficiency. This can be done by finding optimal generators and durations of the evolutions. We present numerical results regarding the preparation of double-bracket iterations, both in ideal cases where the algorithm's setup provides analytical convergence guarantees and in more heuristic cases, where we use an adaptive and variational approach to optimize the generators of the evolutions. As an example, we discuss the efficacy of these optimization strategies when considering a spin-chain Hamiltonian as the target. To propose algorithms that can be executed starting today, fully aware of the limitations of the quantum technologies at our disposal, we finally present a selection of diagonal evolution parametrizations that can be directly compiled into CNOTs and single-qubit rotation gates. We discuss the advantages and limitations of this compilation and propose a way to take advantage of this approach when used in synergy with other existing methods.

quant-ph↗

arXiv2024

Double-bracket quantum algorithms for high-fidelity ground state preparation

Ground state preparation is a central application for quantum computers but remains challenging in practice. In this work, we quantitatively investigate the performance and gate counts of double-bracket quantum algorithms (DBQAs) for ground state preparation. We propose a practical strategy in which DBQAs refine initial state preparation circuits, and we compile them for Heisenberg chains using controlled-Z and single-qubit gates. Warm-started DBQAs consistently improve both the energy and ground-state fidelity relative to the initial states provided by variational ans\"atze, indicating that DBQAs offer an effective unitary synthesis method. To demonstrate compatibility with near-term hardware, we executed a proof-of-concept example on IBM devices. With error mitigation, we observed a statistically significant improvement over the corresponding warm-start circuit. Furthermore, numerical emulations for the same system size indicate that executing DBQAs on Quantinuum's hardware could achieve similar cost-function gains without requiring error mitigation. These findings suggest that DBQAs are a promising approach for enhancing ground-state approximations on near-term quantum devices.

quant-ph↗

arXiv2024

T-Count Optimizing Genetic Algorithm for Quantum State Preparation

Quantum state preparation is a crucial process within numerous quantum algorithms, and the need for efficient initialization of quantum registers is ever increasing as demand for useful quantum computing grows. The problem arises as the number of qubits to be initialized grows, the circuits required to implement the desired state also exponentially increase in size leading to loss of fidelity to noise. This is mainly due to the susceptibility to environmental effects of the non-Clifford T gate, whose use should thus be reduced as much as possible. In this paper, we present and utilize a genetic algorithm for state preparation circuits consisting of gates from the Clifford + T gate set and optimize them in T-Count as to reduce the impact of noise. Whilst the method presented here does not always produce the most accurate circuits in terms of fidelity, it can generate high-fidelity, non-trivial quantum states such as quantum Fourier transform states. In addition, our algorithm does automatically generate fault tolerantly implementable solutions where the number of the most error prone components is reduced. We present an evaluation of the algorithm when trialed against preparing random, Poisson probability distribution, W, GHZ, and quantum Fourier transform states. We also experimentally demonstrate the scalability issues as qubit count increases, which highlights the need for further optimization of the search process.

quant-ph↗

arXiv2021

Flexible Instruction-Set Semantics via Type Classes

Instruction sets, from families like x86 and ARM, are at the center of many ambitious formal-methods projects. Many verification, synthesis, programming, and debugging tools rely on formal semantics of instruction sets, but different tools can use semantics in rather different ways. As a result, a central challenge for that community is how semantics should be written and what techniques should be used to connect them to new use cases. The best-known work applying single semantics across quite-different tools relies on domain-specific languages like Sail, where the language and its translation tools are specialized to the realm of instruction sets. We decided to explore a different approach, with semantics written in a carefully chosen subset of Haskell. This style does not depend on any new language translators, relying instead on parameterization of semantics over type-class instances. As a result, a semantics can be a first-class object within a logic, and application of a semantics for a new kind of tool can be a first-class operation in the logic, allowing sharing of theorems across applications. Our case study is for the open RISC-V instruction-set family, and we have used a single core semantics to support testing, interactive proof, and model checking of both software and hardware. We especially highlight an application of a first-class semantics within Coq that can be instantiated in different ways within one proof: simulation between variants where multiplication is implemented in hardware or in the machine code of a particular software trap handler.

cs.LO↗

arXiv2020

The use of multiple models within an organisation

Organisations, whether in government, industry or commerce, are required to make decisions in a complex and uncertain environment. The way models are used is intimately connected to the way organisations make decisions and the context in which they make them. Typically, in a complex organisation, multiple related models will often be used in support of a decision. For example, engineering models might be combined with financial models and macro-economic models in order to decide whether to invest in new production capability. Different parts of a complex organisation might operate their own related models which might then be presented to a central decision maker. Yet in practice, there is little awareness of the practical challenges of using models in a robust way to support decision making. There is significant scope to improve decision making though an enhanced understanding of the role and limitations of modelling and through the application of cutting edge methodologies and organisational best practice. This report is in the form of a 'white paper', whose purpose is to identify key issues for consideration whist postulating tentative approaches to these issues that might be worthy of further exploration, focussing on both technical and organisational aspects. It begins with a framework for consideration of how model-based decisions are made in organisations. It then looks more closely at the questions of uncertainty and multiple models. It then postulates some technical statistical and organisational approaches for managing some of these issues. Finally, it considers the way forward, and the possible focus for further work.

stat.OT↗

arXiv2019

Resonant absorption in expanding coronal magnetic flux tubes with uniform density

Aims. We investigate the transfer of energy between a standing kink mode and azimuthal Alfven waves within an expanding flux tube. We consider the process of resonant absorption in a loop with a non-uniform Alfven frequency profile but in the absence of a radial density gradient. Methods. Using the MHD code, Lare3d, we model an oscillating magnetic flux tube that expands radially with height. An initially straight loop structure with a magnetic field enhancement is relaxed towards a force-free state before a standing kink mode is introduced. Results. We demonstrate that the transverse gradient in Alfven frequency required for the existence of resonant field lines can be associated with the expansion of a high field-strength flux tube from concentrated flux patches. This allows for the conversion of energy between wave modes even in the absence of the density profile typically assumed in wave heating models. As with standing modes in straight flux tubes, small scales are dominated by the vorticity at the loop apex and by currents at the foot points. The azimuthal wave exhibits the structure of the expanded flux tube and is therefore associated with smaller length scales close to the foot points of the flux tube. Conclusions. Resonant absorption can proceed throughout the corona, even in the absence of dense loop structures. The flux tube and MHD waves considered are difficult to observe and our model highlights how estimating hidden wave power within the solar atmosphere can be problematic. We highlight that, for standing modes, the global properties of field lines are important for resonant absorption and coronal conditions at a single altitude will not fully determine the nature of MHD resonances. We provide a new model in partial response to the criticism that wave heating models cannot self-consistently generate or sustain the density profile upon which they typically rely.

astro-ph.SR↗

arXiv2019

An Energy-Efficient Reconfigurable DTLS Cryptographic Engine for Securing Internet-of-Things Applications

This paper presents the first hardware implementation of the Datagram Transport Layer Security (DTLS) protocol to enable end-to-end security for the Internet of Things (IoT). A key component of this design is a reconfigurable prime field elliptic curve cryptography (ECC) accelerator, which is 238x and 9x more energy-efficient compared to software and state-of-the-art hardware respectively. Our full hardware implementation of the DTLS 1.3 protocol provides 438x improvement in energy-efficiency over software, along with code size and data memory usage as low as 8 KB and 3 KB respectively. The cryptographic accelerators are coupled with an on-chip low-power RISC-V processor to benchmark applications beyond DTLS with up to two orders of magnitude energy savings. The test chip, fabricated in 65 nm CMOS, demonstrates hardware-accelerated DTLS sessions while consuming 44.08 uJ per handshake, and 0.89 nJ per byte of encrypted data at 16 MHz and 0.8 V.

cs.CR↗

arXiv2019

An Energy-Efficient Reconfigurable DTLS Cryptographic Engine for End-to-End Security in IoT Applications

This paper presents a reconfigurable cryptographic engine that implements the DTLS protocol to enable end-to-end security for IoT. This implementation of the DTLS engine demonstrates 10x reduction in code size and 438x improvement in energy-efficiency over software. Our ECC primitive is 237x and 9x more energy-efficient compared to software and state-of-the-art hardware respectively. Pairing the DTLS engine with an on-chip RISC-V allows us to demonstrate applications beyond DTLS with up to 2 orders of magnitude energy savings.

cs.CR↗

arXiv2018

MI6: Secure Enclaves in a Speculative Out-of-Order Processor

Recent attacks have broken process isolation by exploiting microarchitectural side channels that allow indirect access to shared microarchitectural state. Enclaves strengthen the process abstraction to restore isolation guarantees. We propose MI6, an aggressive, speculative out-of-order processor capable of providing secure enclaves under a threat model that includes an untrusted OS and an attacker capable of mounting any software attack currently considered practical, including control flow speculation attacks. MI6 is inspired by Sanctum [16] and extends its isolation guarantee to more realistic memory hierarchies. It also introduces a purge instruction, which is used only when a secure process is scheduled, and implements it for a complex processor microarchitecture. We model the performance impact of enclaves in MI6 through FPGA emulation on AWS F1 FPGAs by running SPEC CINT2006 benchmarks on top of an untrusted Linux OS. Security comes at the cost of approximately 16.4% average slowdown for protected programs.

cs.CR↗

arXiv2018

Constructing a Weak Memory Model

Weak memory models are a consequence of the desire on part of architects to preserve all the uniprocessor optimizations while building a shared memory multiprocessor. The efforts to formalize weak memory models of ARM and POWER over the last decades are mostly empirical -- they try to capture empirically observed behaviors -- and end up providing no insight into the inherent nature of weak memory models. This paper takes a constructive approach to find a common base for weak memory models: we explore what a weak memory would look like if we constructed it with the explicit goal of preserving all the uniprocessor optimizations. We will disallow some optimizations which break a programmer's intuition in highly unexpected ways. The constructed model, which we call General Atomic Memory Model (GAM), allows all four load/store reorderings. We give the construction procedure of GAM, and provide insights which are used to define its operational and axiomatic semantics. Though no attempt is made to match GAM to any existing weak memory model, we show by simulation that GAM has comparable performance with other models. No deep knowledge of memory models is needed to read this paper.

cs.AR↗

arXiv2016

Validating Simplified Processor Models in Architectural Studies

Cycle-accurate software simulation of multicores with complex microarchitectures is often excruciatingly slow. People use simplified core models to gain simulation speed. However, a persistent question is to what extent the results derived from a simplified core model can be used to characterize the behavior of a real machine. We propose a new methodology of validating simplified simulation models, which focuses on the trends of metric values across benchmarks and architectures, instead of errors of absolute metric values. To illustrate this methodology, we conduct a case study using an FPGA-accelerated cycle-accurate full system simulator. We evaluated three cache replacement polices on a 10-stage in-order core model, and then re-conducted all the experiments by substituting a 1-IPC core model for the 10-stage core model. We found that the 1-IPC core model generally produces qualitatively the same results as the accurate core model except for a few mismatches. We argue that most observed mismatches were either indistinguishable from experimental noise or corresponded to the cases where the policy differences even in the accurate model showed inconclusive results. We think it is fair to use simplified core models to study a feature once the influence of the simplification is understood. Additional studies on branch predictors and scaling properties of multithread benchmarks reinforce our argument. However, the validation of a simplified model requires a detailed cycle-accurate model!

cs.AR↗