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At least 109 records · Page 6

Trapped-ion quantum simulation of collective neutrino oscillations

It is well known that the neutrino flavor in extreme astrophysical environments changes under the effect of three contributions: the vacuum oscillation, the interaction with the surrounding matter, and the collective oscillations due to interactions between different neutrinos. The latter adds a nonlinear contribution to the equations of motion, making the description of their dynamics complex. In this work we study various strategies to simulate the coherent collective oscillations of a system of N neutrinos in the two-flavor approximation using quantum computation. This was achieved by using a pair-neutrino decomposition designed to account for the fact that the flavor Hamiltonian, in the presence of the neutrino-neutrino term, presents an all-to-all interaction that makes the implementation of the evolution dependent on the qubit topology. We analyze the Trotter error caused by the decomposition demonstrating that the complexity of the implementation of time evolution scales polynomially with the number of neutrinos and that the noise from near-term quantum device simulation can be reduced by optimizing the quantum circuit decomposition and exploiting a full-qubit connectivity. We find that the gate complexity using second order Trotter-Suzuki formulas scales better with system size than with other decomposition methods such as quantum signal processing. In conclusion, we finally present the application and the results of our algorithm on a real quantum device based on trapped-ion qubits.

79 ASTRONOMY AND ASTROPHYSICS↗

Variational quantum reinforcement learning via evolutionary optimization

Abstract Recent advances in classical reinforcement learning (RL) and quantum computation point to a promising direction for performing RL on a quantum computer. However, potential applications in quantum RL are limited by the number of qubits available in modern quantum devices. Here, we present two frameworks for deep quantum RL tasks using gradient-free evolutionary optimization. First, we apply the amplitude encoding scheme to the Cart-Pole problem, where we demonstrate the quantum advantage of parameter saving using amplitude encoding. Second, we propose a hybrid framework where the quantum RL agents are equipped with a hybrid tensor network-variational quantum circuit (TN-VQC) architecture to handle inputs of dimensions exceeding the number of qubits. This allows us to perform quantum RL in the MiniGrid environment with 147-dimensional inputs. The hybrid TN-VQC architecture provides a natural way to perform efficient compression of the input dimension, enabling further quantum RL applications on noisy intermediate-scale quantum devices.

97 MATHEMATICS AND COMPUTING↗

Imaginary Time Propagation on a Quantum Chip

We report evolution in imaginary time is a prominent technique for finding the ground state of quantum many-body systems, and the heart of a number of numerical methods that have been used with great success in quantum chemistry, condensed matter, and nuclear physics. We propose an algorithm to implement imaginary time propagation on a quantum computer. Our algorithm is devised in the context of an efficient encoding into an optimized gate, drawing on the underlying characteristics of the quantum device of a unitary operation in an extended Hilbert space. However, we prove that for simple problems it can also be successfully applied to standard digital quantum machines. This work paves the way for porting quantum many-body methods based on imaginary-time propagation to near-term quantum devices, enabling the future quantum simulation of the ground states of a broad class of microscopic systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Standard model physics and the digital quantum revolution: thoughts about the interface

Advances in isolating, controlling and entangling quantum systems are transforming what was once a curious feature of quantum mechanics into a vehicle for disruptive scientific and technological progress. Pursuing the vision articulated by Feynman, a concerted effort across many areas of research and development is introducing prototypical digital quantum devices into the computing ecosystem available to domain scientists. Through interactions with these early quantum devices, the abstract vision of exploring classically-intractable quantum systems is evolving toward becoming a tangible reality. Beyond catalyzing these technological advances, entanglement is enabling parallel progress as a diagnostic for quantum correlations and as an organizational tool, both guiding improved understanding of quantum many-body systems and quantum field theories defining and emerging from the standard model. Here, from the perspective of three domain science theorists, this article compiles thoughts about the interface on entanglement, complexity, and quantum simulation in an effort to contextualize recent NISQ-era progress with the scientific objectives of nuclear and high-energy physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A clean ballistic quantum point contact in strontium titanate

The perovskite oxide strontium titanate (SrTiO 3 ) combines electrostatic tunability, superconductivity and spin–orbit coupling, and is of potential use in the development of quantum devices. However, exploring quantum effects in SrTiO 3 nanostructures is challenging because of the presence of disorder. Here, in this work, we report high-mobility, gate-tunable devices in SrTiO 3 that have ballistic constrictions and clean normal-state conductance quantization. Our devices are based on SrTiO 3 two-dimensional electron gas channels that have a thin hafnium oxide barrier layer between the channel and an ionic liquid gate. Conductance plateaus show twofold degeneracy that persists for magnetic fields of at least 5 T. This is above what is expected from the g factors extracted at high fields and could be a signature of electron pairing extending outside the superconducting regime.

36 MATERIALS SCIENCE↗

Error statistics and scalability of quantum error mitigation formulas

Quantum computing promises advantages over classical computing in many problems. Nevertheless, noise in quantum devices prevents most quantum algorithms from achieving the quantum advantage. Quantum error mitigation provides a variety of protocols to handle such noise using minimal qubit resources. While some of those protocols have been implemented in experiments for a few qubits, it remains unclear whether error mitigation will be effective in quantum circuits with tens to hundreds of qubits. In this paper, we apply statistics principles to quantum error mitigation and analyse the scaling behaviour of its intrinsic error. We find that the error increases linearly O(ϵN) with the gate number N before mitigation and sublinearly O(ϵ'N γ ) after mitigation, where γ ≈ 0.5, ϵ is the error rate of a quantum gate, and ϵ' is a protocol-dependent factor. The $\sqrt{N}$ scaling is a consequence of the law of large numbers, and it indicates that error mitigation can suppress the error by a larger factor in larger circuits. We propose the importance Clifford sampling as a key technique for error mitigation in large circuits to obtain this result.

97 MATHEMATICS AND COMPUTING↗

A universal variational quantum eigensolver for non-Hermitian systems

Abstract Many quantum algorithms are developed to evaluate eigenvalues for Hermitian matrices. However, few practical approach exists for the eigenanalysis of non-Hermintian ones, such as arising from modern power systems. The main difficulty lies in the fact that, as the eigenvector matrix of a general matrix can be non-unitary, solving a general eigenvalue problem is inherently incompatible with existing unitary-gate-based quantum methods. To fill this gap, this paper introduces a Variational Quantum Universal Eigensolver (VQUE), which is deployable on noisy intermediate scale quantum computers. Our new contributions include: (1) The first universal variational quantum algorithm capable of evaluating the eigenvalues of non-Hermitian matrices—Inspired by Schur’s triangularization theory, VQUE unitarizes the eigenvalue problem to a procedure of searching unitary transformation matrices via quantum devices; (2) A Quantum Process Snapshot technique is devised to make VQUE maintain the potential quantum advantage inherited from the original variational quantum eigensolver—With additional $$O(log_{2}{N})$$ O ( l o g 2 N ) quantum gates, this method efficiently identifies whether a unitary operator is triangular with respect to a given basis; (3) Successful deployment and validation of VQUE on a real noisy quantum computer, which demonstrates the algorithm’s feasibility. We also undertake a comprehensive parametric study to validate VQUE’s scalability, generality, and performance in realistic applications.

97 MATHEMATICS AND COMPUTING↗

Realizing a topological diode effect on the surface of a topological Kondo insulator

Introducing the concept of topology into material science has sparked a revolution from classic electronic and optoelectronic devices to topological quantum devices. The latter has potential for transferring energy and information with unprecedented efficiency. Here, we demonstrate a topological diode effect on the surface of a three-dimensional material, SmB 6 , a candidate topological Kondo insulator. The diode effect is evidenced by pronounced rectification and photogalvanic effects under electromagnetic modulation and radiation at radio frequency. Our experimental results and modeling suggest that these prominent effects are intimately tied to the spatially inhomogeneous formation of topological surface states (TSS) at the intermediate temperature. This work provides a manner of breaking the mirror symmetry (in addition to the inversion symmetry), resulting in the formation of pn-junctions between puddles of metallic TSS. Further, this effect paves the way for efficient current rectifiers or energy-harvesting devices working down to radio frequency range at low temperature, which could be extended to high temperatures using other topological insulators with large bulk gap.

36 MATERIALS SCIENCE↗

Quantum‐Classical Simulation of Quantum Field Theory by Quantum Circuit Learning

Abstract Quantum circuit learning is employed to simulate quantum field theories (QFTs). Typically, when simulating QFTs with quantum computers, significant challenges are encountered due to the technical limitations of quantum devices when implementing the Hamiltonian using Pauli spin matrices. To address this challenge, quantum circuit learning is leveraged, employing a compact configuration of qubits and low‐depth quantum circuits to predict real‐time dynamics in quantum field theories. The key advantage of this approach is that a single‐qubit measurement can accurately forecast various physical parameters, including fully‐connected operators. To demonstrate the effectiveness of this method, it is used to predict quench dynamics, chiral dynamics and jet production in a 1+1‐dimensional model of quantum electrodynamics. It is found that our predictions closely align with the results of rigorous classical calculations, exhibiting a high degree of accuracy. This hybrid quantum‐classical approach illustrates the feasibility of efficiently simulating large‐scale QFTs on cutting‐edge quantum devices.

Ikeda, Kazuki [Department of Physics University of↗

A Perspective on Quantum Computing Applications in Quantum Chemistry Using 25-100 Logical Qubits

The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owing to the exponential growth of classical resource requirements for simulating quantum systems, quantum chemistry has long been recognized as a natural candidate for quantum computation. This perspective focuses on identifying scientifically meaningful use cases where early fault-tolerant quantum computers, which are considered to be equipped with approximately 25-100 logical qubits, could deliver tangible impact. While recent advances in classical computing have pushed the boundaries of tractable simulations to unprecedented scales, this logical-qubit regime represents the first window where quantum devices can pursue qualitatively distinct strategies, such as polynomial-scaling phase estimation, direct simulation of quantum dynamics, and active-space embedding, that remain challenging for classical solvers, such as multireference charge-transfer and conical-intersection states central to photochemistry and materials design. We highlight near-term opportunities in algorithm and software design, discuss representative chemical problems suited for quantum acceleration, and propose strategic roadmaps and collaborative pathways for advancing practical quantum utility in quantum chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fixed-point quantum circuits for quantum field theories

Renormalization group ideas and effective operators are introduced to efficiently prepare ground states of massive lattice field theories on digital quantum devices. This is accomplished with a systematic approximation through localized unitaries that removes an exponentially costly barrier in the spatial volume of the quantum simulation. With these methods, classically computed ground states in a spatial volume L, containing a few Compton wavelengths, can be used to determine operators for preparing the ground state toward the thermodynamic limit with a precision improving as e –mL on beyond-classical quantum registers. Here, due to the exponential spatial decay of correlations in massive theories and the double exponential suppression of digitization artifacts in the number of qubits representing the scalar field, the derived fixed-point quantum circuits are expected to be relevant for simulations of quantum field theories throughout the evolution from small-scale near-term quantum devices to large-scale fault-tolerant quantum computers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Simulating Alpha Particles Incident on MKID Chips for Quantum Sensitivity Analysis

Superconducting quantum devices, such as microwave kinetic inductance detectors (MKIDs), are highly sensitive instruments used in quantum computing and advanced sensing technologies. However, their extreme sensitivity also makes them vulnerable to background noise from natural sources like radiation. One significant contributor to this noise is alpha particles emitted by 210Po, a radon decay daughter that accumulates on surfaces near the detector. This project investigates how alpha particles emitted from 210Po interact with MKID chips. These particles can deposit energy on the detector surface, disrupting its operation and generating false signals. Understanding the energy and behavior of these particles is crucial for improving the design and reliability of quantum devices. To explore this, we first modeled the decay chain starting from 210Pb to 210Po using differential equations. This allowed us to predict how the activity of alpha-emitting isotopes changes over time, reaching a steady state after about two years. Next, we simulated alpha particle interactions with the MKID chip using the Geant4 software toolkit. We built a detailed computer model of the detector housing, including the copper lid where alpha particles originate, the silicon chip, and a thin aluminum sensor layer. Alpha particles were emitted isotropically from just beneath the copper lid’s surface, mimicking natural decay conditions. The simulation tracked how these particles deposit energy on the chip, generating electron-hole pairs and phonons. The results provide insight into the behavior of the resultant electron-hole pairs and phonons, giving us a clear understanding of the energy deposition distribution on the chip. This work supports efforts to mitigate background noise in superconducting sensors, advancing their use in quantum computing and sensitive physics experiments.

Hall, Matthew [Fermilab; UCLA]↗

Mitigating challenges in aberration-corrected electron-beam lithography on electron-opaque substrates

Aberration-corrected electron-beam lithography (AC-EBL) using ultra-thin electron transparent membranes has achieved single-digit nanometer resolution in two widely used electron-beam resists: poly (methyl methacrylate) (PMMA) and hydrogen silsesquioxane. On the other hand, AC-EBL implementation on thick, electron-opaque substrates is appealing for conventional top-down fabrication of quantum devices with nanometer-scale features. To investigate the performance of AC-EBL on thick substrates, we measured the lithographic point spread function of a 200 keV aberration-corrected scanning transmission electron microscope by defining both positive and negative patterns in PMMA thin films, spin-cast on thick SiO 2 /Si substrates. We present the problems encountered during pre-exposure beam focusing and discuss methods to overcome them. In addition, applying some of these methods using commercial 50 nm thick SiN X membranes with thick Si support frames, we printed arrays of holes in PMMA with pitches around 26 nm on SiN X /Si substrates with increasing Si thickness. Here, our results show that proximity effects from even 50 nm thick SiN X membranes limit hole arrays to 20 nm pitch; however, down to this limit, the effect of the substrate thickness on the pattern quality is minimal. These results highlight the need for novel resists less susceptible to proximity effects, or resists which can be used directly, after development, as the dielectric material in periodic gates in 2D quantum devices.

2D quantum devices↗

Classically verifiable quantum advantage from a computational Bell test

Existing experimental demonstrations of quantum computational advantage have had the limitation that verifying the correctness of the quantum device requires exponentially costly classical computations. Here we propose and analyse an interactive protocol for demonstrating quantum computational advantage, which is efficiently classically verifiable. Our protocol relies on a class of cryptographic tools called trapdoor claw-free functions. Although this type of function has been applied to quantum advantage protocols before, our protocol employs a surprising connection to Bell’s inequality to avoid the need for a demanding cryptographic property called the adaptive hardcore bit, while maintaining essentially no increase in the quantum circuit complexity and no extra assumptions. Leveraging the relaxed cryptographic requirements of the protocol, we present two trapdoor claw-free function constructions, based on Rabin’s function and the Diffie–Hellman problem, which have not been used in this context before. We also present two independent innovations that improve the efficiency of our implementation and can be applied to other quantum cryptographic protocols. First, we give a scheme to discard so-called garbage bits, removing the need for reversibility in the quantum circuits. Second, we show a natural way of performing postselection that reduces the fidelity needed to demonstrate quantum advantage. Combining these results, we describe a blueprint for implementing our protocol on Rydberg atom-based quantum devices, using hardware-native operations that have already been demonstrated experimentally.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Error-mitigated data-driven circuit learning on noisy quantum hardware

Application-level benchmarks measure how well a quantum device performs meaningful calculations. In the case of parameterized circuit training, the computational task is the preparation of a target quantum state via optimization over a loss landscape. This is complicated by various sources of noise, fixed hardware connectivity, and generative modeling, the choice of target distribution. Gradient-based training has become a useful benchmarking task for noisy intermediate-scale quantum computers because of the additional requirement that the optimization step uses the quantum device to estimate the loss function gradient. In this work, we use gradient-based data-driven circuit learning to qualitatively evaluate the performance of several superconducting platform devices and present results that show how error mitigation can improve the training of quantum circuit Born machines with 28 tunable parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Demonstration of the rodeo algorithm on a quantum computer

The rodeo algorithm is an efficient algorithm for eigenstate preparation and eigenvalue estimation for any observable on a quantum computer. This makes it a promising tool for studying the spectrum and structure of atomic nuclei as well as other fields of quantum many-body physics. The only requirement is that the initial state has sufficient overlap probability with the desired eigenstate. While it is exponentially faster than well-known algorithms such as phase estimation and adiabatic evolution for eigenstate preparation, it has yet to be implemented on an actual quantum device. In this work, we apply the rodeo algorithm to determine the energy levels of a random one-qubit Hamiltonian, resulting in a relative error of 0.08% using mid-circuit measurements on the IBM Q device Casablanca. This surpasses the accuracy of directly-prepared eigenvector expectation values using the same quantum device. We take advantage of the high-accuracy energy determination and use the Hellmann-Feynman theorem to compute eigenvector expectation values for a different random one-qubit observable. For the Hellmann-Feynman calculations, we find a relative error of 0.7%. Here, we conclude by discussing possible future applications of the rodeo algorithm for multi-qubit Hamiltonians.

algorithm↗

Roadmap on Atomtronics: State of the art and perspective

Atomtronics deals with matter-wave circuits of ultracold atoms manipulated through magnetic or laser-generated guides with different shapes and intensities. In this way, new types of quantum networks can be constructed in which coherent fluids are controlled with the know-how developed in the atomic and molecular physics community. In particular, quantum devices with enhanced precision, control, and flexibility of their operating conditions can be accessed. Concomitantly, new quantum simulators and emulators harnessing on the coherent current flows can also be developed. Here, the authors survey the landscape of atomtronics-enabled quantum technology and draw a roadmap for the field in the near future. The authors review some of the latest progress achieved in matter-wave circuits' design and atom-chips. Atomtronic networks are deployed as promising platforms for probing many-body physics with a new angle and a new twist. The latter can be done at the level of both equilibrium and nonequilibrium situations. Numerous relevant problems in mesoscopic physics, such as persistent currents and quantum transport in circuits of fermionic or bosonic atoms, are studied through a new lens. The authors summarize some of the atomtronics quantum devices and sensors. Finally, the authors discuss alkali-earth and Rydberg atoms as potential platforms for the realization of atomtronic circuits with special features.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Design & Assembly of Atomically-Precise Quantum Materials & Devices (Final Report)

Atomic-layer honeycomb materials (Xene, where “X” may stand for a number of different elements) are a promising platform for new quantum states. When X is a heavier element such as tin (Sn) or bismuth (Bi), the edges of the honeycomb may conduct electron charge or spin without resistance - an effect that could persist up to room temperature in some cases. The type of edge states, and their robustness at room temperature, depend sensitively on (a) the substrate material that the Xene is sitting on; (b) out-of-plane buckling of the honeycomb structure; (c) the pattern of atoms or molecules sitting atop the honeycomb. This sensitivity suggests that Xene edge states could be tuned and rearranged to construct nanoscale electronic or spintronic devices. We report on theoretical progress in modeling the assembly and structure of Xenes, and their underlying substrates and overlaying atoms. Specifically, we model the stability of Sn atoms forming a single atomic layer (“stanene”), the stability and phase transitions

36 MATERIALS SCIENCE↗