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Even denominator fractional quantum Hall states in higher Landau levels of graphene

A remarkable development in the field of the fractional quantum Hall effect has been the proposal that the 5/2 state observed in the Landau level with orbital index n = 1 of two- dimensional electrons in a GaAs quantum well originates from a chiral p-wave paired state of composite fermions which are topological bound states of electrons and quantized vortices. This state is theoretically described by a “Pfaffian” wave function or its hole partner called the anti-Pfaffian, whose excitations are neither fermions nor bosons but Majorana quasiparticles obeying non-Abelian braid statistics. Here, this has inspired innovative ideas on fault-tolerant topological quantum computation and has also instigated a quest for other states with exotic quasi- particles. Here we report experiments on monolayer graphene that show clear evidence for unexpected even-denominator fractional quantum Hall physics in the n = 3 Landau level. We numerically investigate the known candidate states for even-denominator fractional quantum Hall effect, including the Pfaffian, the particle-hole symmetric Pfaffian, the 221-parton, and several valley / spin singlet states, and conclude that, among these, the 221-parton state is the most plausible candidate to explain the experimentally observed state. Like the Pfaffian, this state is also believed to harbour quasi-particles with non-Abelian braid statistics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Engineering of niobium surfaces through accelerated neutral atom beam technology for quantum applications

A major roadblock to scalable quantum computing is phase decoherence and energy relaxation caused by qubits interacting with defect-related two-level systems (TLSs). Native oxides present on the surfaces of superconducting metals used in quantum devices are acknowledged to be a source of TLS that decrease qubit coherence times. Reducing microwave loss by “surface engineering” (i.e., replacing the uncontrolled native oxide of superconducting metals with a thin, stable surface with predictable characteristics) can be a key enabler for pushing performance forward with devices of higher intrinsic quality factor. In this work, we present a novel approach to replace the native oxide of niobium (typically formed in an uncontrolled fashion when its pristine surface is exposed to air) with an engineered oxide, using a room-temperature process that leverages accelerated neutral atom beam (ANAB) technology at 300 mm wafer scale. This ANAB is composed of a mixture of argon and oxygen, with tunable energy per atom, which is rastered across the wafer surface. The ANAB-engineered Nb-oxide thickness was found to vary from 2 to 6 nm depending on ANAB process parameters. The modeling of variable-energy x-ray photoelectron spectroscopy data confirms the thickness and compositional control of Nb surface oxide by the ANAB process. Furthermore, these results correlate well with those from transmission electron microscopy and x-ray reflectometry. Since ANAB is broadly applicable to material surfaces, the present study indicates its promise for modification of the surfaces of superconducting quantum circuits to achieve longer coherence times.

36 MATERIALS SCIENCE↗

Adaptive mitigation of time-varying quantum noise

Current quantum computers suffer from non-stationary noise channels with high error rates, which undermines their reliability and reproducibility. We propose a Bayesian inference based adaptive algorithm that can learn and mitigate quantum noise in response to changing channel conditions. Our study emphasizes the need for dynamic inference of critical channel parameters to improve program accuracy. We use the Dirichlet distribution to model the stochasticity of the Pauli channel. This allows us to perform Bayesian inference, which can improve the performance of probabilistic error cancellation (PEC) under time-varying noise. Our work demonstrates the importance of characterizing and mitigating temporal variations in quantum noise, which is crucial for developing more accurate and reliable quantum technologies. Our results demonstrate that Bayesian PEC can outperform non-adaptive approaches by a factor of 4.5x when measured using Hellinger distance from the ideal distribution.

Dasgupta, Samudra↗

Qubit Regularization of Quantum Field Theories

To study quantum field theories on a quantum computer, we must begin with Hamiltonians defined on a finite-dimensional Hilbert space and then take appropriate limits. This approach can be seen as a new type of regularization for quantum field theories, which we refer to as qubit regularization. A related finite-dimensional regularization, known as the D-theory approach, was proposed long ago as a general framework for all quantum field theories. In this framework, the dimensionality of the local Hilbert space at each spatial point can increase as needed through an additional flavor index. To reproduce asymptotically free QFTs, most studies assume that qubit-regularized theories require extending the local Hilbert space to infinity. However, contrary to this common belief, recent discoveries in (1+1) dimensions have revealed two examples where asymptotic freedom appears to emerge within a strictly finite-dimensional local Hilbert space through a novel renormalization group (RG) flow. These findings motivate further investigation into whether asymptotically free gauge theories could also emerge within a strictly finite-dimensional local Hilbert space. To support these explorations, we propose an orthonormal basis called the monomer-dimer-tensor-network (MDTN) basis and use it to construct new types of qubit-regularized lattice gauge theories.

Chandrasekharan, Shailesh [Duke Univ., Durham, NC ↗

Federated Quantum Machine Learning

Distributed training across several quantum computers could significantly improve the training time and if we could share the learned model, not the data, it could potentially improve the data privacy as the training would happen where the data is located. One of the potential schemes to achieve this property is the federated learning (FL), which consists of several clients or local nodes learning on their own data and a central node to aggregate the models collected from those local nodes. However, to the best of our knowledge, no work has been done in quantum machine learning (QML) in federation setting yet. In this work, we present the federated training on hybrid quantum-classical machine learning models although our framework could be generalized to pure quantum machine learning model. Specifically, we consider the quantum neural network (QNN) coupled with classical pre-trained convolutional model. Our distributed federated learning scheme demonstrated almost the same level of trained model accuracies and yet significantly faster distributed training. It demonstrates a promising future research direction for scaling and privacy aspects.

97 MATHEMATICS AND COMPUTING↗

Learning thermodynamic master equations for open quantum systems

The characterization of Hamiltonians and other components of open quantum dynamical systems plays a crucial role in quantum computing and other applications. Scientific machine learning techniques have been applied to this problem in a variety of ways, including by modeling with deep neural networks. However, the majority of mathematical models describing open quantum systems are linear, and the natural nonlinearities in learnable models have not been incorporated using physical principles. We present a data-driven model for open quantum systems that includes learnable, thermodynamically consistent terms. The trained model is interpretable, as it directly estimates the system Hamiltonian and linear components of coupling to the environment. We validate the model on synthetic two and three-level data, as well as experimental two-level data collected from a quantum device at Lawrence Livermore National Laboratory.

Mathematics and Computing↗

Quantum Speedup for Aeroscience and Engineering

Algorithms and hardware for quantum computing (QC) are reaching a critical stage in their development and have the potential to generate a paradigm shift in computing capability across a range of fields. Opportunities are growing for genuine impact of these systems over a timescale of 10-15 years, and there has been significant investment both from government agencies and private industry in its development. However, utilization of quantum phenomena is extraordinarily challenging due to its delicate nature and difficulties in measurement and control. A clear path exists toward demonstrating the advantages of QC over existing high-performance computing for some physics and materials science problems but addressing practical computational challenges in other fields, though promising, is at an early stage of development. Reaching the next level of development will require strategic coordination between physicists, computer & information scientists, mathematicians, and engineers, in order to transition this technology from the laboratory to robust and scalable computations for practical problems, especially those of interest to the aeroscience and engineering community. This community has been relying on high-performance computing heavily and will surely want to be informed of the developments in QC. This survey introduces the background and current state of the art in QC, as well as its perceived opportunities and challenges.

Peyman Givi↗

Surpassing millisecond coherence in on chip superconducting quantum memories by optimizing materials and circuit design

The performance of superconducting quantum circuits for quantum computing has advanced tremendously in recent decades; however, a comprehensive understanding of relaxation mechanisms does not yet exist. In this work, we utilize a multimode approach to characterizing energy losses in superconducting quantum circuits, with the goals of predicting device performance and improving coherence through materials, process, and circuit design optimization. Using this approach, we measure significant reductions in surface and bulk dielectric losses by employing a tantalum-based materials platform and annealed sapphire substrates. With this knowledge we predict the relaxation times of aluminum- and tantalum-based transmon qubits, and find that they are consistent with experimental results. We additionally optimize device geometry to maximize coherence within a coaxial tunnel architecture, and realize on-chip quantum memories with single-photon Ramsey times of 2.0 – 2.7 ms, limited by their energy relaxation times of 1.0 – 1.4 ms. These results demonstrate an advancement towards a more modular and compact coaxial circuit architecture for bosonic qubits with reproducibly high coherence.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Quantum Tensor-Product Decomposition from Choi-State Tomography

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 decomposition. While quantum technological implementations of the former are thoroughly studied, entangling properties on the operator level are harder to extract in the quantum computational framework because of the exponential nature of sample complexity. Here, we present an algorithm for unbalanced partitions into a small subsystem and a large one (the environment) to compute the tensor-product decomposition of a unitary the effect of which on the small subsystem is captured in classical memory, while the effect on the environment is accessible as a quantum resource. This quantum algorithm may be used to make predictions about operator nonlocality and effective open quantum dynamics on a subsystem, as well as for finding low-rank approximations and low-depth compilations of quantum circuit unitaries. We demonstrate the method and its applications on a time-evolution unitary of an isotropic Heisenberg model in two dimensions. Published by the American Physical Society 2024

Mansuroglu, Refik (ORCID:000000017352513X)↗

Q-OPT:Quantum Optimization Toolkit

SF-2025-003 Quantum computing has the potential to solve classical optimization problems. To bring these algorithms into practical use, a comprehensive, high-performance and user-friendly toolkit is essential. The Q-OPT: Quantum Optimization Toolkit is a collection of software tools designed to support complete end-to-end framework for quantum optimization.

Hovland, Paul [Argonne National Laboratory (ANL), ↗

Degradation of Ta 2 O 5 / SiO 2 dielectric cavity mirrors in ultra-high vacuum

In order for optical cavities to enable strong light-matter interactions for quantum metrology, networking, and scalability in quantum computing systems, their mirrors must have minimal losses. However, high-finesse dielectric cavity mirrors can degrade in ultra-high vacuum (UHV), increasing the challenges of upgrading to cavity-coupled quantum systems. We observe the optical degradation of high-finesse dielectric optical cavity mirrors after high-temperature UHV bake in the form of a substantial increase in surface roughness. We provide an explanation of the degradation through atomic force microscopy (AFM), X-ray fluorescence (XRF), selective wet etching, and optical measurements. We find the degradation is explained by oxygen reduction in Ta 2 O 5 followed by growth of tantalum sub-oxide defects with height to width aspect ratios near ten. We discuss the dependence of mirror loss on surface roughness and finally give recommendations to avoid degradation to allow for quick adoption of cavity-coupled systems.

Optics↗

Benchmarking a Tunable Quantum Neural Network on Trapped-Ion and Superconducting Hardware

We implement a quantum generalization of a neural network on trapped-ion and IBM superconducting quantum computers to classify MNIST images, a common benchmark in computer vision. The network feedforward involves qubit rotations whose angles depend on the results of measurements in the previous layer. The network is trained via simulation, but inference is performed experimentally on quantum hardware. The classical-to-quantum correspondence is controlled by an interpolation parameter, $a$, which is zero in the classical limit. Increasing $a$ introduces quantum uncertainty into the measurements, which is shown to improve network performance at moderate values of the interpolation parameter. We then focus on particular images that fail to be classified by a classical neural network but are detected correctly in the quantum network. For such borderline cases, we observe strong deviations from the simulated behavior. We attribute this to physical noise, which causes the output to fluctuate between nearby minima of the classification energy landscape. Such strong sensitivity to physical noise is absent for clear images. We further benchmark physical noise by inserting additional single-qubit and two-qubit gate pairs into the neural network circuits. Our work provides a springboard toward more complex quantum neural networks on current devices: while the approach is rooted in standard classical machine learning, scaling up such networks may prove classically non-simulable and could offer a route to near-term quantum advantage.

FOS: Physical sciences↗

Electron-impact vibrational relaxation in high-temperature nitrogen

Vibrational relaxation process of N2 molecules by electron-impact is examined for the future planetary entry environments. Multiple-quantum transitions from excited states to higher/lower states are considered for the electronic ground state of the nitrogen molecule N2 (X 1Sigma-g(+)). Vibrational excitation and deexcitation rate coefficients obtained by computational quantum chemistry are incorporated into the 'diffusion model' to evaluate the time variations of vibrational number densities of each energy state and total vibrational energy. Results show a non-Boltzmann distribution of number densities at the earlier stage of relaxation, which in turn suppresses the equilibrium process but affects little the time variation of total vibrational energy. An approximate rate equation and a corresponding relaxation time from the excited states, compatible with the system of flow conservation equations, are derived. The relaxation time from the excited states indicates the weak dependency of the initial vibrational temperature. The empirical curve-fit formula for the improved e-V relaxation time is obtained.

Lee, Jong-Hun↗

Holographic scattering requires a connected entanglement wedge

In AdS/CFT, there can exist local 2-to-2 bulk scattering processes even when local scattering is not possible on the boundary; these have previously been studied in con- nection with boundary correlation functions. We show that boundary regions associated with these scattering configurations must have O(1/G N ) mutual information, and hence a connected entanglement wedge. One of us previously argued for this statement from the boundary theory using operational tools in quantum information theory. We improve that argument to make it robust to small errors and provide a proof in the bulk using focusing arguments in general relativity. We also provide a direct link to entanglement wedge reconstruction by showing that the bulk scattering region must lie inside the con- nected entanglement wedge. Our construction implies the existence of nonlocal quantum computation protocols that are exponentially more efficient than the optimal protocols currently known.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

2D-EFICACY: Control of Metastable 2D Carbide[1]Chalcogenide Heterolayers: Strain and Moire Engineering

The experimental isolation of graphene led to the discovery of an entirely new world of two-dimensional (2D) materials in which the 2D nature often leads to emergent behaviors not seen in bulk systems. 2D transition metal dichalcogenides (TMDs) exhibit physico-chemical properties that depend on the transition metal, polymorph, thickness, and presence and type of defects. Recently, a group of thin (10-100nm) transition metal carbides (TMCs), such as Mo2C, has been synthesized that exhibit a thickness-dependent superconducting critical temperature (Tc). These thin TMCs are different from MXenes, another class of 2D materials consisting of few layers of nitrides or carbides (<5nm) produced by chemical etching and delamination. The goal of this renewal proposal is to combine experiment and computation to synthesize and elucidate the guiding principles that control the growth, orientation and strain of heterostacks of thin TMCs and TMDs composed with Nb, Ti and W. We expect to stabilize metastable hybrid phases of TMCs sandwiched between TMDs (H-TMD/Cs) with unprecedented physico-chemical properties. As part of previous DOE-funded work by the Terrones/Sinnott groups, thin (10-100 nm thick) Mo2C flakes were successfully synthesized by chemical vapor deposition (CVD). By subsequently exposing Mo2C to H2S, partial chalcogenization was achieved, resulting in heterostacks of MoCx phases and MoS2. The formation of MoS2 led to a deficiency of Mo atoms in the underlying Mo2C, resulting in an inhomogeneous phase change from α-Mo2C to γ’-MoCx and then to γ-MoC. The γ’-MoCx is a strained metastable phase and the heterostack of all three phases demonstrated an increased Tc relative to that of α-Mo2C, from 4 to 6K; its interleaved layered structure consisting of superconducting and semiconducting phases is ideal for future studies of Josephson junction series arrays. Moiré patterns in these heterostacked systems could result in new phenomena, as moiré patterns in bilayer graphene showed unconventional superconductivity and moiré excitons have been observed in twisted TMD heterobilayers. The scientific hypothesis of the proposed synergistic computational and experimental research is that orientation and strain control within confined thin metastable TMCs, sandwiched by stable phases of TMCs and layered TMDs, will depend on kinetic and thermodynamic “knobs” that include fast temperature changes, chalcogen diffusion through preferred crystallographic planes, reaction times, pressure, reactive atmosphere, precursors, and surfactants, which will also tailor properties such as superconductivity, magnetism, ferroelectricity, piezoelectricity, and catalytic performance. We will develop the guiding principles for the synthesis and stabilization of metastable H-TMD/Cs based on Nb, Ti and W. In order to validate the hypothesis, four tasks are proposed: The first task will synthesize ultra-thin TMCs based on Nb, W and Ti, by: 1) adapting the CVD method used for Mo2C, 2) plasma assisted CVD, 3) defect-mediated CVD processes, and 4) cryo-milling of carbide powders. The second task will accomplish the synthesis and basic physico-chemical characterizations of H-TMD/Cs by chalcogenization of the materials synthesized in task one, and by carbonization of TMDs. H-TMD/Cs will also be investigated for their suitability in energy conversion applications such as supercapacitors, Li and multivalent ion batteries, and electrocatalysts, topics of interest to DoE. These tasks will be carried out in close conjunction with density functional theory (DFT) calculations with insights into energetics, lattice parameters, stability, phase diagrams, band structures, and density of states of H-TMD/Cs. The third task will characterize and evaluate strain and moiré patterns at the interfaces of different H-TMD/Cs by high-resolution scanning transmission electron microscopy (HR-STEM), scanning tunneling microscopy (STM), and conductive tip atomic force microscopy. Nudged elastic band calculations with DFT will be performed to understand the chalcogen diffusion process, which will provide insights into the interfaces between different phases of TMCs and TMDs. The fourth task aims at quantifying the stability and dynamics of H-TMD/Cs by in-situ TEM and Raman studies under heating, strain, and electrical biasing. Phonon calculations using DFT will provide a basis for interpreting Raman spectra. This coherent framework involving synthesis, characterization, and computation will result in a broad scientific impact for energy related applications. The ability to develop new H-TMD/Cs will enhance a range of applications that include batteries, catalysts, switches, sensors, quantum computing components and smart coatings.

2-Dimensional materials↗

2D-EFICACY: Control of Metastable 2D Carbide Chalcogenide Heterolayers: Strain and Moire Engineering

The experimental isolation of graphene led to the discovery of an entirely new world of two-dimensional (2D) materials in which the 2D nature often leads to emergent behaviors not seen in bulk systems. 2D transition metal dichalcogenides (TMDs) exhibit physico-chemical properties that depend on the transition metal, polymorph, thickness, and presence and type of defects. Recently, a group of thin (10-100nm) transition metal carbides (TMCs), such as Mo 2 C, has been synthesized that exhibit a thickness-dependent superconducting critical temperature (Tc). These thin TMCs are different from MXenes, another class of 2D materials consisting of few layers of nitrides or carbides (<5nm) produced by chemical etching and delamination. The goal of this renewal proposal is to combine experiment and computation to synthesize and elucidate the guiding principles that control the growth, orientation and strain of heterostacks of thin TMCs and TMDs composed with Nb, Ti and W. We expect to stabilize metastable hybrid phases of TMCs sandwiched between TMDs (H-TMD/Cs) with unprecedented physico-chemical properties. As part of previous DOE-funded work by the Terrones/Sinnott groups, thin (10-100 nm thick) Mo 2 C flakes were successfully synthesized by chemical vapor deposition (CVD). By subsequently exposing Mo 2 C to H 2 S, partial chalcogenization was achieved, resulting in heterostacks of MoCx phases and MoS 2 . The formation of MoS 2 led to a deficiency of Mo atoms in the underlying Mo 2 C, resulting in an inhomogeneous phase change from α-Mo 2 C to γ’-MoCx and then to γ-MoC. The γ’-MoCx is a strained metastable phase and the heterostack of all three phases demonstrated an increased Tc relative to that of α-Mo 2 C, from 4 to 6K; its interleaved layered structure consisting of superconducting and semiconducting phases is ideal for future studies of Josephson junction series arrays. Moiré patterns in these heterostacked systems could result in new phenomena, as moiré patterns in bilayer graphene showed unconventional superconductivity and moiré excitons have been observed in twisted TMD heterobilayers. The scientific hypothesis of the proposed synergistic computational and experimental research is that orientation and strain control within confined thin metastable TMCs, sandwiched by stable phases of TMCs and layered TMDs, will depend on kinetic and thermodynamic “knobs” that include fast temperature changes, chalcogen diffusion through preferred crystallographic planes, reaction times, pressure, reactive atmosphere, precursors, and surfactants, which will also tailor properties such as superconductivity, magnetism, ferroelectricity, piezoelectricity, and catalytic performance. We will develop the guiding principles for the synthesis and stabilization of metastable H-TMD/Cs based on Nb, Ti and W. In order to validate the hypothesis, four tasks are proposed: The first task will synthesize ultra-thin TMCs based on Nb, W and Ti, by: 1) adapting the CVD method used for Mo 2 C, 2) plasma assisted CVD, 3) defect-mediated CVD processes, and 4) cryo-milling of carbide powders. The second task will accomplish the synthesis and basic physico-chemical characterizations of H-TMD/Cs by chalcogenization of the materials synthesized in task one, and by carbonization of TMDs. H-TMD/Cs will also be investigated for their suitability in energy conversion applications such as supercapacitors, Li and multivalent ion batteries, and electrocatalysts, topics of interest to DoE. These tasks will be carried out in close conjunction with density functional theory (DFT) calculations with insights into energetics, lattice parameters, stability, phase diagrams, band structures, and density of states of H-TMD/Cs. The third task will characterize and evaluate strain and moiré patterns at the interfaces of different H-TMD/Cs by high-resolution scanning transmission electron microscopy (HR-STEM), scanning tunneling microscopy (STM), and conductive tip atomic force microscopy. Nudged elastic band calculations with DFT will be performed to understand the chalcogen diffusion process, which will provide insights into the interfaces between different phases of TMCs and TMDs. The fourth task aims at quantifying the stability and dynamics of H-TMD/Cs by in-situ TEM and Raman studies under heating, strain, and electrical biasing. Phonon calculations using DFT will provide a basis for interpreting Raman spectra. This coherent framework involving synthesis, characterization, and computation will result in a broad scientific impact for energy related applications. The ability to develop new H-TMD/Cs will enhance a range of applications that include batteries, catalysts, switches, sensors, quantum computing components and smart coatings.

2-Dimensional Materials↗

Engineering Dynamical Sweet Spots to Protect Qubits from 1/$f$ Noise

Protecting superconducting qubits from low-frequency noise is essential for advancing superconducting quantum computation. Based on the application of a periodic drive field, we develop a protocol for engineering dynamical sweet spots which reduce the susceptibility of a qubit to low-frequency noise. Using the framework of Floquet theory, we prove rigorously that there are manifolds of dynamical sweet spots marked by extrema in the quasi-energy differences of the driven qubit. In particular, for the example of fluxonium biased slightly away from half a flux quantum, we predict an enhancement of pure-dephasing by three orders of magnitude. Employing the Floquet eigenstates as the computational basis, we show that high-fidelity single- and two-qubit gates can be implemented while maintaining dynamical sweet-spot operation. We further confirm that qubit readout can be performed by adiabatically mapping the Floquet states back to the static qubit states, and subsequently applying standard measurement techniques. Our work provides an intuitive tool to encode quantum information in robust, time-dependent states, and may be extended to alternative architectures for quantum information processing.

Huang, Ziwen↗

Using Quasiparticle Poisoning To Detect Photons

According to a proposal, a phenomenon associated with excitation of quasiparticles in certain superconducting quantum devices would be exploited as a means of detecting photons with exquisite sensitivity. The phenomenon could also be exploited to perform medium-resolution spectroscopy. The proposal was inspired by the observation that Coulomb blockade devices upon which some quantum logic gates are based are extremely sensitive to quasiparticles excited above the superconducting gaps in their leads. The presence of quasiparticles in the leads can be easily detected via the charge states. If quasiparticles could be generated in the leads by absorption of photons, then the devices could be used as very sensitive detectors of electromagnetic radiation over the spectral range from x-rays to submillimeter waves. The devices in question are single-Cooper-pair boxes (SCBs), which are mesoscopic superconducting devices developed for quantum computing. An SCB consists of a small superconducting island connected to a reservoir via a small tunnel junction and connected to a voltage source through a gate capacitor. An SCB is an artificial two-level quantum system, the Hamiltonian of which can be controlled by the gate voltage. One measures the expected value of the charge of the eigenvectors of this quantum system by use of a radio-frequency single-electron transistor. A plot of this expected value of charge as a function of gate voltage resembles a staircase that, in the ideal case, consists of steps of height 2 e (where e is the charge of one electron). Experiments have shown that depending on the parameters of the device, quasiparticles in the form of "broken" Cooper pairs present in the reservoir can tunnel to the island, giving rise to steps of 1 e. This effect is sometimes called "poisoning." Simulations have shown that an extremely small average number of quasiparticles can generate a 1-e periodic signal. In a device according to the proposal, this poisoning would be turned to advantage. Depending on the wavelength, an antenna or other component would be used to couple radiation into the reservoir, wherein the absorption of photons would break Cooper pairs, thereby creating quasiparticles that, in turn, would tunnel to the island, creating a 1-e signal. On the basis of conservative estimates of device parameters derived from experimental data and computational simulations that fit the data, it has been estimated that the noise equivalent power of a device according to the proposal could be as low as 6 10(exp -22) W/Hz(exp 1/2). It has also been estimated that the spectroscopic resolution (photon energy divided by increment of photon energy) of such a device in visible light would exceed 100.

Echternach, Pierre↗