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View article: Double-bracket algorithm for quantum signal processing without post-selection
Double-bracket algorithm for quantum signal processing without post-selection Open
Quantum Signal Processing (QSP), a framework for implementing matrix-valued polynomials, is a fundamental primitive in various quantum algorithms. Despite its versatility, a potentially underappreciated challenge is that all systematic pro…
View article: When quantum resources backfire: Non-gaussianity and symplectic coherence in noisy bosonic circuits
When quantum resources backfire: Non-gaussianity and symplectic coherence in noisy bosonic circuits Open
Analyzing the impact of noise is of fundamental importance to understand the advantages provided by quantum systems. While the classical simulability of noisy discrete-variable systems is increasingly well understood, noisy bosonic circuit…
View article: Advantage for Discrete Variational Quantum Algorithms in Circuit Recompilation
Advantage for Discrete Variational Quantum Algorithms in Circuit Recompilation Open
The relative power of quantum algorithms, using an adaptive access to quantum devices, versus classical post-processing methods that rely only on an initial quantum data set, remains the subject of active debate. Here, we present evidence …
View article: On the Complexity of Quantum States and Circuits from the Orthogonal and Symplectic Groups
On the Complexity of Quantum States and Circuits from the Orthogonal and Symplectic Groups Open
Understanding the complexity of quantum states and circuits is a central challenge in quantum information science, with broad implications in many-body physics, high-energy physics and quantum learning theory. A common way to model the beh…
View article: Does provable absence of barren plateaus imply classical simulability?
Does provable absence of barren plateaus imply classical simulability? Open
A large amount of effort has recently been put into understanding the barren plateau phenomenon. In this perspective article, we face the increasingly loud elephant in the room and ask a question that has been hinted at by many but not exp…
View article: Resource-Efficient Simulations of Particle Scattering on a Digital Quantum Computer
Resource-Efficient Simulations of Particle Scattering on a Digital Quantum Computer Open
We develop and demonstrate methods for simulating the scattering of particle wave packets in the interacting Thirring model on digital quantum computers, with hardware implementations on up to 80 qubits. We identify low-entanglement time s…
View article: Grover's algorithm is an approximation of imaginary-time evolution
Grover's algorithm is an approximation of imaginary-time evolution Open
We reveal the power of Grover's algorithm from thermodynamic and geometric perspectives by showing that it is a product formula approximation of imaginary-time evolution (ITE), a Riemannian gradient flow on the special unitary group. This …
View article: Pauli Propagation: A Computational Framework for Simulating Quantum Systems
Pauli Propagation: A Computational Framework for Simulating Quantum Systems Open
Classical methods to simulate quantum systems are not only a key element of the physicist's toolkit for studying many-body models but are also increasingly important for verifying and challenging upcoming quantum computers. Pauli propagati…
View article: On Dequantization of Supervised Quantum Machine Learning via Random Fourier Features
On Dequantization of Supervised Quantum Machine Learning via Random Fourier Features Open
In the quest for quantum advantage, a central question is under what conditions can classical algorithms achieve a performance comparable to quantum algorithms--a concept known as dequantization. Random Fourier features (RFFs) have demonst…
View article: Role of scrambling and noise in temporal information processing with quantum systems
Role of scrambling and noise in temporal information processing with quantum systems Open
Scrambling quantum systems have been demonstrated as effective substrates for temporal information processing. While their role in providing rich feature maps has been widely studied, a theoretical understanding of their performance in tem…
View article: Variational optical phase learning on a continuous-variable quantum compiler
Variational optical phase learning on a continuous-variable quantum compiler Open
Quantum process learning is a fundamental primitive that draws inspiration from machine learning with the goal of better studying the dynamics of quantum systems. One approach to quantum process learning is quantum compilation, whereby an …
View article: On fundamental aspects of quantum extreme learning machines
On fundamental aspects of quantum extreme learning machines Open
Quantum extreme learning machines (QELMs) have emerged as a promising framework for quantum machine learning. Their appeal lies in the rich feature map induced by the dynamics of a quantum substrate—the quantum reservoir—and the efficient …
View article: Exploiting symmetries in nuclear Hamiltonians for ground state preparation
Exploiting symmetries in nuclear Hamiltonians for ground state preparation Open
The Lipkin and Agassi models are simplified nuclear models that provide natural test beds for quantum simulation methods. Prior work has investigated the suitability of the variational quantum eigensolver (VQE) to find the ground state of …
View article: Variational Quantum Simulation: A Case Study for Understanding Warm Starts
Variational Quantum Simulation: A Case Study for Understanding Warm Starts Open
The barren plateau phenomenon, characterized by loss gradients that vanish exponentially with system size, poses a challenge to scaling variational quantum algorithms. Here we explore the potential of warm starts, whereby one initializes c…
View article: Simulating quantum circuits with arbitrary local noise using Pauli Propagation
Simulating quantum circuits with arbitrary local noise using Pauli Propagation Open
We present a polynomial-time classical algorithm for estimating expectation values of arbitrary observables on typical quantum circuits under any incoherent local noise, including non-unital or dephasing. Although previous research demonst…
View article: Myths around quantum computation before full fault tolerance: What no-go theorems rule out and what they don't
Myths around quantum computation before full fault tolerance: What no-go theorems rule out and what they don't Open
In this perspective article, we revisit and critically evaluate prevailing viewpoints on the capabilities and limitations of near-term quantum computing and its potential transition toward fully fault-tolerant quantum computing. We examine…
View article: Double-bracket quantum algorithms for quantum imaginary-time evolution
Double-bracket quantum algorithms for quantum imaginary-time evolution Open
Efficiently preparing approximate ground-states of large, strongly correlated systems on quantum hardware is challenging and yet nature is innately adept at this. This has motivated the study of thermodynamically inspired approaches to gro…
View article: Efficient quantum-enhanced classical simulation for patches of quantum landscapes
Efficient quantum-enhanced classical simulation for patches of quantum landscapes Open
Understanding the capabilities of classical simulation methods is key to identifying where quantum computers are advantageous. Not only does this ensure that quantum computers are used only where necessary, but also one can potentially ide…
View article: High-fidelity dimer excitations using quantum hardware
High-fidelity dimer excitations using quantum hardware Open
The quantum simulation of entangled spin systems can play a central role in quantum magnetic materials discovery. Additionally, the simulation of spectroscopic signatures, such as the dynamical structure factor accessed in inelastic neutro…
View article: Exact gradients for linear optics with single photons
Exact gradients for linear optics with single photons Open
Though parameter shift rules have drastically improved gradient estimation methods for several types of quantum circuits, leading to improved performance in downstream tasks, so far they have not been transferable to linear optics with sin…
View article: Classically estimating observables of noiseless quantum circuits
Classically estimating observables of noiseless quantum circuits Open
We present a classical algorithm based on Pauli propagation for estimating expectation values of arbitrary observables on random unstructured quantum circuits across all circuit architectures and depths, including those with all-to-all con…
View article: Quantum Convolutional Neural Networks are (Effectively) Classically Simulable
Quantum Convolutional Neural Networks are (Effectively) Classically Simulable Open
Quantum Convolutional Neural Networks (QCNNs) are widely regarded as a promising model for Quantum Machine Learning (QML). In this work we tie their heuristic success to two facts. First, that when randomly initialized, they can only opera…
View article: Double-bracket quantum algorithms for high-fidelity ground state preparation
Double-bracket quantum algorithms for high-fidelity ground state preparation Open
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 groun…
View article: Quantum Computing for High-Energy Physics: State of the Art and Challenges
Quantum Computing for High-Energy Physics: State of the Art and Challenges Open
Quantum computers offer an intriguing path for a paradigmatic change of computing in the natural sciences and beyond, with the potential for achieving a so-called quantum advantage—namely, a significant (in some cases exponential) speedup …
View article: Quantum Tensor-Product Decomposition from Choi-State Tomography
Quantum Tensor-Product Decomposition from Choi-State Tomography Open
The Schmidt decomposition is the go-to tool for measuring bipartite entanglement of pure quantum states. Similarly, it is possible to study the entangling features of a quantum operation using its operator-Schmidt or tensor-product decompo…
View article: Exponential concentration in quantum kernel methods
Exponential concentration in quantum kernel methods Open
Kernel methods in Quantum Machine Learning (QML) have recently gained significant attention as a potential candidate for achieving a quantum advantage in data analysis. Among other attractive properties, when training a kernel-based model …
View article: Barren Plateaus in Variational Quantum Computing
Barren Plateaus in Variational Quantum Computing Open
Variational quantum computing offers a flexible computational paradigm with applications in diverse areas. However, a key obstacle to realizing their potential is the Barren Plateau (BP) phenomenon. When a model exhibits a BP, its paramete…
View article: Variational quantum simulation: a case study for understanding warm starts
Variational quantum simulation: a case study for understanding warm starts Open
The barren plateau phenomenon, characterized by loss gradients that vanish exponentially with system size, poses a challenge to scaling variational quantum algorithms. Here we explore the potential of warm starts, whereby one initializes c…