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S-band high-gradient accelerating structures were proposed to accelerate protons from 30 to 230 MeV for a compact proton therapy linac in Institute of Modern Physics. A backward traveling wave structure and a single-periodic magnetically coupled standing wave structure were designed, and differences between these two structures were analyzed to select a more suitable one for the proton therapy linac. In this paper, a novel single-periodic magnetically coupled standing-wave accelerating structure was studied, with an optimized nose cone that related to a smaller peak surface electric field and higher shunt impedance, with the reduced number of coupling holes and mechanical von Mises stress thus making it possible for higher duty factor and longer rf pulse operation, also with larger coupling holes and improved cell-to-cell coupling thus making this structure suitable for operating in π mode. An 11-cell high-power prototype for β=0.26 particles was developed with an active length of 143 mm. This prototype cavity is supposed to operate at an accelerating gradient of 30 MV/m with 0.1% duty factor, corresponding to a maximum surface electric field of 105 MV/m and a peak rf power of 3.43 MW. Cavity design, optimization, manufacture, rf measurement, and high-power test will be discussed in this paper.

A dual-energy electron storage ring is a novel concept initially proposed to cool hadron beams at high energies. The design consists of two closed rings operating at significantly different energies: the low-energy ring and the high-energy ring. These two rings are connected by an energy recovery linac (ERL) that provides the necessary energy difference. The ERL features superconducting radio-frequency (SRF) cavities that first accelerate the beam from the low energy E_{L} to the high energy E_{H} and then decelerate the beam from E_{H} to E_{L} in the next pass. The different SRF cavities in the ERL section can be adjusted based on the applications. In this paper, we present a possible layout of a dual-energy electron storage ring. The preliminary optics of the ring is designed to optimize chromaticity correction, dynamic aperture, momentum aperture, beam lifetime, radiation damping, and intrabeam scattering effects. The primary focus of this paper is on the stability conditions and beam dynamics studies associated with this storage ring.

Numerical optimizations on couplers of the traveling-wave (TW) accelerating structures usually require lots of calculation resources. This paper proposes a new technique for matching couplers to an accelerating structure in a more efficient and accurate way. It combines improved Kroll method with improved Kyhl method, thereby simplifying simulation process while achieving a high accuracy. This paper also presents the detailed design on couplers for a C-band constant-gradient (CG) accelerating structure based on this new technique. Such a new technique can be widely used for any TW accelerating structures working at different frequencies of S-band, C-band, and X-band including CG, constant-impedance (CI), and other structures with either electric couplers or magnetic couplers.

Rotating gantries are commonly used in ion-therapy facilities to assist and support optimizing the dose distribution delivered to the patient. They are installed at the end of the beamlines and rotated mechanically in the treatment room. In synchrotron-based facilities, the gantries must be able to transport slowly extracted beams with essentially different emittance patterns in the two transverse planes. Such beams will be referred to as the asymmetric beams. A special device called rotator has been proposed as a possible solution. The worldwide first beamline with the rotator has been recently commissioned. The original rotator concept uses an “external” rotator that is a part (a module) of the beamline the gantry is connected to. In this paper, a novel gantry ion-optical concept integrating the rotator optics into the gantry optics is introduced. The first-order gantry transfer matrix satisfies the so-called sigma-matching ion-optical constraints, and—at the same time—it possesses the format of a rotator transfer matrix. The rotator-matching and the sigma-matching principles are combined in the gantry transfer matrix, which means that the sigma-matching gantry acts simultaneously as a rotator without the need for an extra rotator device. In addition, scattering in the gantry nozzle is used to balance the asymmetric beam emittances in the two transverse planes without an additional scattering foil. In this way, the presented ion-optical concept combines all three known matching techniques—the sigma matching, the rotator matching, and the scattering-foil matching—within the gantry beam transport system. Such a beam transport system provides the best matching result and full angular independence of the beam parameters at the gantry isocenter. It also makes it possible to optimize the beam parameters not only at the gantry isocenter but also at the beam monitors located in the gantry nozzle without increasing the number of gantry quadrupoles. There are two possible versions of such gantry optics: the point-to-point and the parallel-to-point optics. They both are presented in this paper. Theoretical calculations are supported by beam transport simulations performed with the winagile code. Feasibility of the newly proposed ion-optical concept is demonstrated on the MedAustron proton gantry. However, it can be applied to any rotating gantry at any ion-therapy facility. The presented design is the first rotatorlike gantry ion-optical concept worldwide.

Quantum computation is expected to accelerate certain computational tasks over classical counterparts. Its most primitive advantage is its ability to sample from classically intractable probability distributions. A promising approach to make use of this fact is the so-called quantum-enhanced Markov-chain Monte Carlo (qe-MCMC) method [D. Layden et al., Nature (London) 619, 282 (2023)0028-083610.1038/s41586-023-06095-4], which uses outputs from quantum circuits as the proposal distributions. In this paper, we propose the use of a quantum alternating operator ansatz (QAOA) for qe-MCMC and provide a strategy to optimize its parameters to improve convergence speed while keeping its depth shallow. The proposed QAOA-type circuit is designed to satisfy the specific constraint which qe-MCMC requires with arbitrary parameters. Through our extensive numerical analysis, we find a correlation in a certain parameter range between an experimentally measurable value, acceptance rate of MCMC, and the spectral gap of the MCMC transition matrix, which determines the convergence speed. This allows us to optimize the parameter in the QAOA circuit and achieve quadratic speedup in convergence. Since MCMC is used in various areas such as statistical physics and machine learning, this paper represents an important step toward realizing practical quantum advantage with currently available quantum computers through qe-MCMC.

Quantum computing technology has the potential to revolutionize the simulation of materials and molecules in the near future. A primary challenge in achieving near-term quantum advantage is effectively mitigating the noise effects inherent in current quantum processing units (QPUs). This challenge is also decisive in the context of quantum-classical hybrid schemes employing variational quantum eigensolvers (VQEs) that have attracted significant interest in recent years. In this paper, we present a method that employs parametric Gaussian process regression (GPR) within an active learning framework to mitigate noise in quantum computations, focusing on VQEs. Our approach, grounded in probabilistic machine learning, exploits a custom prior based on the VQE ansatz to capture the underlying correlations between VQE outputs for different variational parameters, thereby enhancing both accuracy and efficiency. We demonstrate the effectiveness of our method on a two-site Anderson impurity model and a eight-site Heisenberg model, using the IBM open-source quantum computing framework, Qiskit, showcasing substantial improvements in the accuracy of VQE outputs while reducing the number of direct QPU energy evaluations. This paper contributes to the ongoing efforts in quantum-error mitigation and optimization, bringing us a step closer to realizing the potential of quantum computing in quantum matter simulations.

Searching via quantum walk is a topic that has been extensively studied. Most previous results provide approximate solutions, while in this paper we prove an algorithm that can find a marked vertex certainly. We adopt the coined discrete-time quantum walk (DTQW) model with adjusted operators and prove that, on complete bipartite graphs, when parameters are set properly, coined DTQW can deterministically find a marked vertex, i.e., the success probability is exactly 1. Before this paper there have been results of an alternating continuous-time quantum walk method that achieve deterministic spatial search, but this paper provides a deterministic quantum spatial search result via DTQW, while maintaining a quadratic speedup compared to classical algorithms. We also provide the quantum circuit implementation.

Variational quantum algorithms rely on the optimization of parameterized quantum circuits in noisy settings. The commonly used back-propagation procedure in classical machine learning is not directly applicable in this setting due to the collapse of quantum states after measurements. Thus, gradient estimations constitute a significant overhead in a gradient-based optimization of such quantum circuits. This paper introduces a random coordinate descent algorithm as a practical and easy-to-implement alternative to the full gradient descent algorithm. This algorithm only requires one partial derivative at each iteration. Motivated by the behavior of measurement noise in the practical optimization of parameterized quantum circuits, this paper presents an optimization problem setting that is amenable to analysis. Under this setting, the random coordinate descent algorithm exhibits the same level of stochastic stability as the full gradient approach, making it as resilient to noise. The complexity of the random coordinate descent method is generally no worse than that of the gradient descent and can be much better for various quantum optimization problems with anisotropic Lipschitz constants. Theoretical analysis and extensive numerical experiments validate our findings.

In this paper, we have demonstrated that optically generated fictitious magnetic fields can be utilized to extend the lifetime of quantum memories in cold atomic ensembles. All the degrees of freedom of an AC Stark shift, such as polarization, spatial profile, and temporal waveform, can be readily controlled in a precise manner. Temporal fluctuations over several experimental cycles and spatial inhomogeneities along a cold atomic gas have been compensated by an optical beam. The advantage of employing fictitious magnetic fields for quantum storage lies in the speed and spatial precision with which these fields can be synthesized. Our simple and versatile technique can find widespread application in coherent pulse and single-photon storage across various atomic species.

Imaginary-time response functions of finite-temperature quantum systems are often obtained with methods that exhibit stochastic or systematic errors. Reducing these errors comes at a large computational cost—in quantum Monte Carlo simulations, the reduction of noise by a factor of two incurs a simulation cost of a factor of four. In this paper, we relate certain imaginary-time response functions to an inner product on the space of linear operators on Fock space. We then show that data with noise typically does not respect the positive definiteness of its associated Gramian. The Gramian has the structure of a Hankel matrix. As a method for denoising noisy data, we introduce an alternating projection algorithm that finds the closest positive definite Hankel matrix consistent with noisy data. We test our methodology at the example of fermion Green's functions for continuous-time quantum Monte Carlo data and show remarkable improvements of the error, reducing noise by a factor of up to 20 in practical examples. We argue that Hankel projections should be used whenever finite-temperature imaginary-time data of response functions with errors is analyzed, be it in the context of quantum Monte Carlo, quantum computing, or in approximate semianalytic methodologies.

The orbital Hall effect can generate currents of angular momentum more efficiently than the spin Hall effect in most metals. However, so far, it has only been understood as a steady-state phenomenon. In this theoretical study, the orbital Hall effect is extended into the time domain. We investigate the orbital angular momenta and their currents induced by a femtosecond laser pulse in a Cu nanoribbon. Our numerical simulations provide detailed insights into the laser-driven electron dynamics on ultrashort timescales with atomic resolution. The ultrafast orbital Hall effect described in this paper is consistent with the familiar pictorial representation of the static orbital Hall effect, but we also find pronounced differences between physical quantities that carry orbital angular momentum and those that carry charge. For example, there are deviations in the time series of the respective currents. This paper lays the foundations for investigating ultrafast Hall effects in confined metallic systems.

This paper provides an overview of the worldwide first commissioning of a gantry beamline with a rotator at the MedAustron synchrotron-based proton/ion cancer therapy facility in Wiener Neustadt, Austria. The gantry beamline consists of the high energy beam transfer (HEBT) line and the gantry beam transport system. It transports the beam from the synchrotron to the gantry-room isocenter. The HEBT transports the beam from the synchrotron to the gantry entrance, which is the coupling point between the HEBT and the gantry. The rotator is one of the HEBT modules, thus it is an integral part of the gantry beamline. The MedAustron rotator is the worldwide first rotator system used to match slowly extracted asymmetric beams from the synchrotron to the rotating gantry. In this paper, main attention is paid to ion-optical and beam-alignment aspects of the beamline commissioning. A novel orbit-correction and beam-alignment technique has been developed specifically for the beamline with the rotator. While the theoretical concept of the rotator has existed for almost two decades, the MedAustron rotator is the first hardware implementation of this concept all over the world. The presented overview of the beamline commissioning includes a description of the principal technical solutions and main results of the first beam-transport measurements. Since the measured beam size and beam position agree well with theoretical predictions, one can conclude that the proof-of-concept of the rotator-matching has been successfully accomplished.

The High Intensity Proton Accelerator facility (HIPA) delivers a 590 MeV cw (50.6 MHz) proton beam with up to 1.4 MW beam power (2.4 mA) to spallation and meson production targets serving particle physics experiments and material research. The main accelerator is the ring cyclotron, an isochronous proton machine accelerating an injected 72 MeV beam to a final 590 MeV. A few meters downstream of the ring cyclotron, an electrostatic beam splitter was installed in the 1980s and originally designed to peel off from a 200 μA beam up to 20 μA (12 kW beam power). Future initiatives will also make use of the splitter. Specifically, as part of the Isotope and Muon Production using Advanced Cyclotron and Target technologies (IMPACT) upgrade project, Targeted Alpha Tumour Therapy and Other Oncological Solutions (TATTOOS), an online isotope separation facility will allow to produce promising radionuclides for diagnosis and therapy of cancer in quantities sufficient for clinical studies. The TATTOOS facility includes a dedicated beamline intended to operate at a beam intensity of 100 μA (60 kW beam power), requiring continuous splitting of the high-power main beam via the splitter. As a step forward toward reaching the desired beam intensity, a beam study was carried out to test the viability of the existing splitter for TATTOOS. The results of this study show that a record of 90 μA (53 kW beam power) was peeled off a horizontally and vertically enlarged beam by the splitter. The successful beam strategy employed during the study as well as the results of several key measurements are presented in this paper, with particular emphasis on diagnostic measurements. Additionally, to support the measurements, a computational model of the splitter has been implemented using Monte Carlo simulation tools, including realistic geometry, electrostatic fields, beam optics, and power deposition calculations. Overall, the results of this paper show that through the combination of beam measurements and simulations, the existing splitter can be used to reach the 100-μA beam intensity requirement for TATTOOS.

Coherent-one-way (COW) quantum key distribution (QKD) is a significant communication protocol that has been implemented experimentally and deployed in practical products due to its simple equipment requirements. However, existing security analyses of COW-QKD either provide a short transmission distance or lack immunity against coherent attacks in the finite-key regime. In this paper, we present a tight finite-key security analysis within the universally composable framework for a variant of COW-QKD, which has been proven to extend the secure transmission distance in the asymptotic case. We combine the quantum leftover hash lemma and entropic uncertainty relation to derive the key rate formula. When estimating statistical parameters, we use the recently proposed Kato's inequality to ensure security against coherent attacks and achieve a higher key rate. Our paper confirms the security and feasibility of COW-QKD for practical application and lays the foundation for further theoretical study and experimental implementation.

From bacteria and sperm cells to artificial microrobots, self-propelled microscopic objects at low Reynolds numbers often perceive fluctuating mechanical and chemical stimuli and contact exterior wall boundaries both in nature and the laboratory. In this paper, we theoretically investigate the fundamental features of microswimmers by focusing on their reciprocal deformation. Although the scallop theorem prohibits the net locomotion of reciprocal microswimmers, by analyzing a two-sphere swimmer model, we show that in a fluctuating and geometrically confined environment, reciprocal deformations can afford a statistically average displacement. After designing the shape gait, a reciprocal swimmer can migrate in any direction, even in the statistical sense, while the statistical average of passive rigid particles statistically diffuses in a particular direction in the presence of external boundaries. To elucidate this symmetry breakdown, by introducing an impulse response function, we derive a general formula for predicting the nonzero net displacement of a reciprocal swimmer. Using this theory, we determine the relation between the shape gait and net locomotion as well as the net diffusion constant increase and decrease, owing to a reciprocal deformation. Based on these findings and a theoretical formulation, we provide a fundamental basis for environment-coupled statistical locomotion. Thus, this paper is valuable for understanding biophysical phenomena in fluctuating environments, designing artificial microrobots, and conducting laboratory experiments.

The standard model of quantum circuits assumes operations are applied in a fixed sequential “causal” order. In recent years, the possibility of relaxing this constraint to obtain causally indefinite computations has received significant attention. The quantum switch, for example, uses a quantum system to coherently control the order of operations. Several ad hoc computational and information-theoretical advantages have been demonstrated, raising questions as to whether advantages can be obtained in a more unified complexity theoretic framework. In this paper, we approach this problem by studying the query complexity of Boolean functions under general higher-order quantum computations. To this end, we generalize the framework of query complexity from quantum circuits to quantum supermaps to compare different models on an equal footing. We show that the recently introduced class of quantum circuits with quantum control of causal order cannot lead to any reduction in query complexity, and that any potential advantage arising from causally indefinite supermaps can be bounded by the polynomial method, as is the case with quantum circuits. Nevertheless, we find some functions for which the minimum error with which they can be computed using two queries is strictly lower when exploiting causally indefinite supermaps.

[This paper is part of the Focused Collection in Investigating and Improving Quantum Education through Research.] When thinking about measurement uncertainty in a laboratory experiment that features quantum mechanical effects, it is important to consider both the physical principles of underlying quantum theory (e.g., the uncertainty due to quantum mechanical superposition states) as well as the limitations of the measurement (e.g., the spread in outcomes due to instrumental imperfections). Prior research has found student difficulties with these sources of uncertainty both individually and in students’ ability to distinguish between them. Additionally, students are less likely to access ideas related to experimental uncertainty in quantum mechanical contexts unless explicitly prompted. In this work, we have developed a simulation-homework activity focused on the Stern-Gerlach experiment to help students develop an understanding for the different ways that modifying the quantum state, improving the experimental setup, or collecting more data, will affect the resulting outcome distribution. The activity uses a purpose-built interactive simulation, coupled with homework questions grounded in the literature on student thinking about uncertainty. We analyze the effectiveness of the activity with students in junior-level undergraduate quantum mechanics courses using pre- and post-testing. The results indicate that the activity was successful in helping students distinguish between quantum mechanical uncertainty and uncertainty caused by instrumental imperfections, and in increasing the accessibility of instrumental limitations in this context. The activity can thus support student understanding of the core concept of quantum uncertainty, as well as link between the often abstract nature of quantum theory and laboratory experiments with their limitations.

Polarized x rays or gamma rays generated from inverse Compton scattering (ICS) sources are high-brightness, quasimonochromatic, and polarization-tunable and are widely applied in medical imaging, material science, and nuclear physics research. In this paper, to simulate ICS between electron beams and polarized laser beams, a Monte Carlo simulation code has been developed and implemented based on the geant4 toolkit. This code considers the polarization as well as the bandwidth of incident laser beams. The code is benchmarked by comparing its simulation results with those from the well-known Monte Carlo tool called cain and experimental results. The comparisons show that this code accurately reproduces the scattered photons, demonstrating its potential for various ICS-based applications.

Physics Education Research has a rich history of identifying common student ideas about specific physics topics. In the context of electric circuits, existing research on students’ ideas has primarily focused on misconceptions, misunderstandings, and difficulties. In this paper, we take a resource-oriented approach to identifying common student ideas about circuits by characterizing ideas we see as generative “seeds of science” that could form the basis of more sophisticated understandings. Based on our analysis of 1557 university physics student responses to five conceptual questions, we identify four common resources for understanding circuits.

Recent developments in the field of quantum machine learning have promoted the idea of incorporating physical symmetries in the structure of quantum circuits. A crucial milestone in this area is the realization of S_{n}-permutation equivariant quantum neural networks (QNNs) that are equivariant under permutations of input objects. In this paper, we focus on encoding the rotational symmetry of point cloud datasets into the QNN. The key insight of the approach is that all rotationally invariant functions with vector inputs are equivalent to a function with inputs of vector inner products. We provide a structure of the QNN that is exactly invariant to both rotations and permutations, with its efficacy demonstrated numerically in the problems of two-dimensional image classifications and identifying high-energy particle decays, produced by proton-proton collisions, with the SO(1,3) Lorentz symmetry.

Using a waveguide in a THz FEL has been shown to maximize the coupling and enable efficient extraction of relativistic electron beam energy from a single passage through a tapered helical undulator. An oscillator configuration can further boost energy extraction above the single-pass limits and open the door toward very high average power THz sources. Embedding the undulator in an oscillator cavity is particularly useful in combination with high repetition rate electron sources, even if at reduced peak brightness, since recycling a fraction of the radiation as an intense seed can compensate for lower single-pass gain. In this paper, we investigate the efficiency scaling of a tapering-enhanced waveguide oscillator, showcasing its capability for frequency-tuning operation and high-efficiency operation at different wavelengths. Using a thermionic-driven beamline equipped with compression elements, numerical start-to-end simulation results indicate a 16% efficiency at 200 GHz and a 2.1% efficiency at 1.5 THz, resulting in kW-level average power out-coupled in radiation pulses with few hundred μJ energy and tens of MW peak power.

[This paper is part of the Focused Collection in Investigating and Improving Quantum Education through Research.] With the current growth in quantum information science and technology (QIST), there is an increasing need to prepare precollege students for postsecondary QIST study and careers. This mixed methods, explanatory sequential research focused on students’ affective outcomes from a one-week, 25-h summer program for U.S. high school students in grades 10–12. The workshop structure was based upon psychosocial theories of self-determination and planned behavior, where QIST aspirations may be facilitated and viewed as achievable choices if students acquire disciplinary knowledge, self-efficacy, normative expectancy of their capacity in the field, and awareness of vocational roles. The program featured lectures, demonstrations, and hands-on experiences in classical and quantum physics and quantum computing. Students’ attitudes toward QIST (N=77)—including self-efficacy, self-concept, relevance, career aspirations, and perceptions of quantitative fluency—showed improvement with a medium effect size, even though treatment students entered the program with more positive QIST attitudes when compared with a control group of high school physics students (N=65). Postprogram interviews with n=12 participants identified several explanatory themes: (i) Students tended to comprehend classical and quantum topics taught through multiple representations, regardless of whether they had taken physics previously; (ii) students experienced some challenges with mathematics and science concepts that support quantum understanding, yet they revealed a willingness to learn new concepts outside of their comfort zone; (iii) students expressed motivation for pursuing science, technology, engineering, and mathematics and/or quantum-related careers in the future, as well as increased QIST self-concept, largely through understanding the relevance of QIST in solving technological problems; and (iv) students reported increased self-efficacy in understanding QIST topics and performing related tasks. This informal summer program showed promise in promoting positive student attitudes toward QIST, a critical emerging field in advancing technological solutions for global challenges.

Existing theories of structural adaptation in biological flow networks are largely concerned with steady flows. However, biological networks are composed of elastic vessels, and many are driven by a pulsatile or periodic source, leading to spatiotemporal variations in the pressure and flow fields on short time-scales within each vessel. Here, we investigate the mathematical problem of how long-term adaptation in elastic networks is impacted by short-term pulsatile dynamics at the level of individual vessels. Using a a minimal one-loop network, we show that pulsatility gives rise to resonances that stabilize the loop for a much broader range of metabolic cost functions than predicted by existing theories. Our paper emphasizes the importance of correctly capturing the interplay of the short and long time-scales for a more realistic treatment of adaptation in periodically driven elastic flow networks.

Subsystem quantum error-correcting codes typically involve measuring a sequence of noncommuting parity check operators. They can sometimes exhibit greater fault tolerance than conventional subspace codes, which use commuting checks. However, unlike subspace codes, it is unclear if subsystem codes—in particular their advantages—can be understood in terms of ground-state properties of a physical Hamiltonian. In this paper, we address this question for the three-dimensional subsystem toric code (3D STC), as recently constructed by Kubica and Vasmer [Nat. Commun. 13, 6272 (2022)2041-172310.1038/s41467-022-33923-4], which exhibits single-shot error correction. Motivated by a conjectured relation between single-shot properties and thermal stability, we study the zero- and finite-temperature phases of an associated noncommuting Hamiltonian. By mapping the Hamiltonian model to a pair of 3D Z_{2} gauge theories coupled by a kinetic constraint, we find various phases at zero temperature, all separated by first-order transitions: There are 3D toric code-like phases with deconfined point-like excitations in the bulk, and there are phases with a confined bulk supporting a 2D toric code on the surface when appropriate boundary conditions are chosen. The latter is similar to the surface topological order present in 3D STC. However, the similarities between the single-shot correction in 3D STC and the confined phases are only partial: they share the same sets of degrees of freedom, but they are governed by different dynamical rules. Instead, we argue that the process of single-shot error correction can more suitably be associated with a path (rather than a point) in the zero-temperature phase diagram, a perspective, which inspires alternative measurement sequences enabling single-shot error correction. Moreover, since none of the above-mentioned phases survives at nonzero temperature, the single-shot error-correction property of the code does not imply thermal stability of the associated Hamiltonian phase.

The communities of practice (COP) framework describes learning as a process of navigating one’s position of membership within a community of professionals pursuing a set of common goals using established practices. As students navigate their membership within a community like a physics research group, they develop a mental model of the community of practice and use this model to guide their future career decisions. Drawing has been shown to illustrate students’ perspectives and experiences, offering important benefits as a source of qualitative information. In this proof-of-concept paper, we explore how a drawing survey can be used to identify elements of a student’s COP model in the context of a research group. We describe the development and validation of this drawing survey using the response process evaluation method. This method establishes the degree to which students interpret survey prompts as intended. We then review a sample of seven student drawings made in response to the survey to investigate the degree to which the survey generates sufficient data to examine a student’s COP model. Finally, we demonstrate a use case examining N=23 drawings that allow us to identify patterns and possible differences in responses from different student groups (physics majors and biology majors). We then reflect on this use of a drawing survey by highlighting important aspects of the process and discussing limitations.

In this paper, we present a Monte Carlo event generator for radiative Bhabha scattering, based on the method of equivalent photons, and optimized for multiturn tracking simulations in the xsuite framework. We demonstrate the accuracy of the event generator with successful benchmarks of the luminosity and event cross section against currently existing alternative tools. Consequently, we use it to investigate existing estimates of the radiative Bhabha scattering beam lifetime at the FCC-ee, as well as the impact of radiative Bhabha scattering on the beam dynamics, using full nonlinear tracking models.

We present a thorough theoretical and experimental investigation of photoionization time delays in the N_{2}O molecule. Our theory provides actual XUV+IR time-resolved photoelectron spectra as measured in real reconstruction of attosecond beating by interference of two-photon transitions (RABBIT) experiments. This requires not only accounting for the interaction between the XUV field and the neutral molecule, but also between the IR field and the ejected electron, which is only possible through explicit evaluation of a large number of dipole couplings between molecular electronic continuum states. To compare with the results of these calculations we have performed RABBIT experiments in which the ejected electron and the resulting ionic fragments are measured in coincidence, thus allowing us to obtain photoionization delays for a particular orientation of the molecule with respect to the polarization of the XUV and IR fields. We have found very good agreement between calculated and measured RABBIT spectra for both nondissociative and dissociative ionization channels. In particular, we unambiguously show a photoionization delay of about 60 as in the vicinity of a well-known shape resonance of N_{2}O in the nondissociative ionization channel. More importantly, we show a dramatic effect of the IR field in the orientation-resolved ionization delays in the whole photon energy range investigated in this paper (18–40 eV), even at the level of relative ionization delays (i.e., delays referred to an internal reference delay) where the effect of the IR field is generally assumed to cancel out. Finally, we explicitly show that the problem of spectral congestion inherent to most molecular systems, which usually prevents extraction of photoionization delays, is substantially alleviated by resolving the molecular orientation or, ideally, by resolving both the molecular orientation and the electron emission angle, where access to perfectly isolated ionization channels is possible at specific angles.

Quantum computers are inherently affected by noise. While in the long term, error correction codes will account for noise at the cost of increasing physical qubits, in the near term, the performance of any quantum algorithm should be tested and simulated in the presence of noise. As noise acts on the hardware, the classical simulation of a quantum algorithm should not be agnostic on the platform used for the computation. In this paper, we apply the recently proposed noisy gates approach to efficiently simulate noisy optical circuits described in the dual rail framework. The evolution of the state vector is simulated directly, without requiring the mapping to the density matrix framework. Notably, we test the method on both the gate-based and measurement-based quantum computing models, showing that the approach is very versatile. We also evaluate the performance of a photonic variational quantum algorithm to solve the MAX-2-CUT problem. In particular we design and simulate an ansatz, which is resilient to photon losses up to p∼10^{−3} making it relevant for near-term applications.

The world’s first 1.3 GHz cryomodule containing eight 9-cell superconducting radio-frequency (rf) cavities treated by medium-temperature furnace baking (mid-T bake) was developed at the Institute of High Energy Physics, Chinese Academy of Sciences. The 9-cell cavities in the cryomodule achieved an unprecedented high average intrinsic quality factor (Q_{0}) of 3.8×10^{10} at 16 MV/m and 3.6×10^{10} at 21 MV/m in the horizontal test. The cryomodule can operate stably up to a total continuous wave rf voltage greater than 193 MV, with an average cavity usable accelerating gradient of more than 23 MV/m. The results significantly exceed the specifications of Circular Electron Positron Collider and Dalian advanced light source and the other high repetition rate free electron laser facilities [Linac Coherent Light Source II (LCLS-II), LCLS-II-high energy, Shanghai High Repetition Rate X-ray FEL and Extreme Light Facility, Shenzhen Superconducting Soft X-Ray Free Electron Laser, etc.]. There is evidence that the mid-T bake cavity may not require fast cooldown or long processing time in the cryomodule. This paper reviews the cryomodule performance and discusses some important issues in cryomodule assembly and testing.

Estimating properties of quantum states via randomized measurements has become a significant part of quantum information science. In this paper, we design an innovative approach leveraging metasurfaces to perform randomized measurements on photonic qubits, together with error mitigation techniques that suppress realistic metasurface measurement noise. Through fidelity and purity estimation, we confirm the capability of metasurfaces to implement randomized measurements and the unbiased nature of our error-mitigated estimator. Our findings show the potential of metasurface-based randomized measurement schemes in achieving robust and resource-efficient estimation of quantum state properties.

Harmonic analysis has provided powerful tools to accurately determine the tune from turn-by-turn data originating from numerical simulations or beam measurements in circular accelerators and storage rings. Methods that have been developed since the 1990s are suitable for stationary signals, i.e., time series whose properties do not vary with time and are represented by stationary signals. However, it is common experience that accelerator physics is a rich source of time series in which the signal amplitude varies over time. Furthermore, the properties of the amplitude variation of the signal often contain essential information about the phenomena under consideration. In this paper, a novel approach is presented, suitable for determining the tune of a nonstationary signal, which is based on the use of the Hilbert transform. The accuracy of the proposed methods is assessed in detail, and an application to the analysis of beam data collected at the CERN Large Hadron Collider is presented and discussed in detail.

In this study, we have explored the effectiveness of two instructional approaches in the context of the motion of objects falling at terminal speed in the presence of air resistance. We ground these instructional approaches in dual-process theories of reasoning, which assert that human cognition relies on two thinking processes. Dual-process theories suggest multiple possible avenues by which instruction might impact student reasoning. In this paper, we compare two possible instructional approaches: one designed to reinforce the normative approach (improving the outputs of the intuitive process) and another that guides students to reflect on and analyze their initial ideas (supporting the analytic process). The results suggest that for students who have already demonstrated a minimum level of requisite knowledge, instruction that supports analysis of their likely intuitive mental model leads to greater learning benefits in the short term than instruction that focuses solely on providing practice with the normative mindware. These results have implications for the design of instructional materials and help to demonstrate how dual-process theories can be leveraged to explain the success of existing research-based materials.

Ultracold fermionic atoms, having two valence electrons, exhibit a distinctive internal state structure, wherein the nuclear spin becomes decoupled from the electronic degrees of freedom in the ground electronic state. Consequently, the nuclear spin states are well isolated from the environment, rendering these atomic systems an opportune platform for quantum computation and quantum simulations. Coupling with off-resonance light is an essential tool to selectively and coherently manipulate the nuclear spin states. In this paper, we present a systematic derivation of the effective Hamiltonian for the nuclear spin states of ultracold fermionic atoms due to such an off-resonance light. We obtain compact expressions for the scalar, vector, and tensor light shifts taking into account both linear and quadratic contributions to the hyperfine splitting. The analysis has been carried out using the Green operator approach and solving the corresponding Dyson equation. Finally, we analyze different scenarios of light configurations which lead to the vector- and tensor-light shifts, as well as the pure spin-orbit coupling for the nuclear spin.

This paper supports the idea that some out-of-equilibrium systems can be described by universality classes. A specific out-of-equilibrium fusing particles model is studied in detail, resulting in a method for determining the number and mass of the final particles based solely on the initial conditions, eliminating the need to evolve the particle system. This method reveals the basis for a universality class encompassing theorem, which is developed to define other models within the same universality class. This result establishes an infinite number of models with the same behavior and scaling, two of which are described in detail.

Beam-driven plasma wakefield acceleration (PWFA) is a promising technique to generate high-energy electron bunches for future electron-positron colliders. Longitudinal shaping of high-charge drive beam is highly desired for achieving high-transformer ratio and loading high-charge witness beam. However, the existing shaping schemes either focused on relatively low-charge bunch shaping or accompanied with significant charge-loss rate (typically over 50%). In this paper, a coherent-synchrotron-radiation-free shaping scheme based on velocity modulation is proposed to generate a high-charge beam with a linearly ramped profile. A >10 kA-peak-current shaped beam containing >50 nC charge with a low charge-loss rate is demonstrated by a start-to-end simulation, and the tunabilities of the beam charge and the peak current, and the robustness of the proposed shaping scheme are also discussed. When loaded by a 3 nC witness beam, a >GV/m accelerating electric field with a transformer ratio larger than 4 can be achieved in a uniform plasma for the shaped drive beam, providing the possibility of high-transformer-ratio PWFA for a high-charge beam.

We investigate how squeezing techniques can improve the measurement precision in multiphase quantum metrology. While these methods are well studied and effectively used in single-phase estimations, their usage in multiphase situations has yet to be examined. We fill this gap by investigating the mechanism of quantum enhancement in the multiphase scenarios. Our analysis provides theoretical and numerical insights into the optimal condition for achieving the quantum Cramér-Rao bound, helping us understand the potential and mechanism for quantum-enhanced multiphase estimations with squeezing. In this paper, we open possibilities for advancements in quantum metrology and sensing technologies.

In this paper, we develop a novel method to solve problems involving quantum optical systems coupled to coherent quantum feedback loops featuring time delays. Our method is based on exact mappings of such non-Markovian problems to equivalent Markovian driven dissipative quantum many-body problems. In this work, we show that the resulting Markovian quantum many-body problems can be solved (numerically) exactly and efficiently using tensor network methods for a series of paradigmatic examples, consisting of driven quantum systems coupled to waveguides at several distant points. In particular, we show that our method allows solving problems in so far inaccessible regimes, including problems with arbitrary long time delays and arbitrary numbers of excitations in the delay lines. We obtain solutions for the full real-time dynamics as well as the steady state in all these regimes. Finally, motivated by our results, we develop a novel mean-field approach, which allows us to find the solution semianalytically, and we identify parameter regimes where this approximation is in excellent agreement with our tensor network results.

One can improve predictability in the unknown domain by combining forecasts of imperfect complex computational models using a Bayesian statistical machine learning framework. In many cases, however, the models used in the mixing process are similar. In addition to contaminating the model space, the existence of such similar, or even redundant, models during the multimodeling process can result in misinterpretation of results and deterioration of predictive performance. In this paper we describe a method based on the principal component analysis that eliminates model redundancy. We show that by adding model orthogonalization to the proposed Bayesian model combination framework, one can arrive at better prediction accuracy and reach excellent uncertainty quantification performance.

A light source project named very compact inverse Compton scattering gamma-ray source (VIGAS) is under development at Tsinghua University. VIGAS aims to generate monochromatic high-energy gamma rays by colliding 350-MeV electron beams with 400-nm laser photons within a 12-m beamline. To produce a high-energy electron beam in such a compact space, the system consists of an S-band high-brightness injector and six X-band high-gradient accelerating structures. The goal of the X-band structure is to operate at a high gradient of 80 MV/m. Therefore, we adopts the constant gradient traveling wave approach, where the iris from the first cell to the end cell is tapered. The structure has 72 cells, including 70 cells and 2 couplers, so we named it XT72. The frequency of XT72 is selected to 11.424 GHz, and the 2π/3 mode is adopted. In this paper, we present a comprehensive study covering the detailed design, fabrication, rf tuning, and high-power test results of the first XT72. Additionally, we compare the performance of this structure to that of the previous constant impedance structure. Our results demonstrate that the XT72 is capable of operating at an 80-MV/m gradient with a lower breakdown rate. This advancement paves the way for the development of VIGAS project and contributes to the wider application of X-band room-temperature high-gradient structures in compact accelerator facilities.

Probabilistic inference is a fundamental task in modern machine learning. Recent advances in tensor network (TN) contraction algorithms have enabled the development of better exact inference methods. However, many common inference tasks in probabilistic graphical models (PGMs) still lack corresponding TN-based adaptations. In this paper, we advance the connection between PGMs and TNs by formulating and implementing tensor-based solutions for the following inference tasks: (A) computing the partition function, (B) computing the marginal probability of sets of variables in the model, (C) determining the most likely assignment to a set of variables, (D) the same as (C) but after having marginalized a different set of variables, and (E) generating samples from a learned probability distribution using a generalized method. Our study is motivated by recent technical advances in the fields of quantum circuit simulation, quantum many-body physics, and statistical physics. Through an experimental evaluation, we demonstrate that the integration of these quantum technologies with a series of algorithms introduced in this study significantly improves the performance efficiency of existing methods for solving probabilistic inference tasks.

In solution, DNA, the “most important molecule of life,” is a highly charged macromolecule that bears a unit of negative charge on each phosphate of its sugar-phosphate backbone. Although partially compensated by counterions (cations of the solution) adsorbed at or condensed near it, DNA still produces a substantial electric field in its vicinity, which is screened by buffer electrolytes at longer distances from the DNA. This electric field is experienced by any charged or dipolar species approaching and interacting with the DNA. So far, such a field has been explored predominantly within the scope of a primitive model of the electrolytic solution, not considering more complicated structural effects of the water solvent. In this paper, we investigate the distribution of electric field around DNA using linear response nonlocal electrostatic theory, applied here for helix-specific charge distributions, and compare the predictions of such a theory with specially performed, fully atomistic, large-scale, molecular dynamics simulations. Both approaches are applied to unravel the role of the structure of water at close distances to and within the grooves of a DNA molecule in the formation of the electric field. As predicted by the theory and reported by the simulations, the main finding of this study is that oscillations in the electrostatic potential distribution are present around DNA, caused by the overscreening effect of structured water. Surprisingly, electrolyte ions at physiological concentrations do not strongly disrupt these oscillations and are rather distributed according to these oscillating patterns, indicating that water structural effects dominate the short-range electrostatics. We also show that (i) structured water adsorbed in the grooves of DNA leads to a positive electrostatic potential core relative to the bulk, (ii) the Debye length some 10 Å away from the DNA surface is reduced, effectively renormalized by the helical pitch of the DNA molecule, and (iii) Lorentzian contributions to the nonlocal dielectric function of water, effectively reducing the dielectric constant close to the DNA surface, enhance the overall electric field. The impressive agreement between the atomistic simulations and the developed theory substantiates the use of nonlocal electrostatics when considering solvent effects in molecular processes in biology.

A recently introduced classical simulation method for universal quantum computation with magic states operates by repeated sampling from probability functions [M. Zurel et al. PRL 260404 (2020)]. This method is closely related to sampling algorithms based on Wigner functions, with the important distinction that Wigner functions can take negative values obstructing the sampling. Indeed, negativity in Wigner functions has been identified as a precondition for a quantum speed-up. However, in the present method of classical simulation, negativity of quasiprobability functions never arises. This model remains probabilistic for all quantum computations. In this paper, we analyze the amount of classical data that the simulation procedure must track. We find that this amount is small. Specifically, for any number n of magic states, the number of bits that describe the quantum system at any given time is 2n^{2}+O(n).

Landau levels are the eigenstates of a charged particle in two dimensions under a magnetic field and are at the heart of the integer and fractional quantum Hall effects, which are two prototypical phenomena showing topological features. Following recent discoveries of fractional quantum Hall phases in van der Waals materials, there is a rapid progress in understanding of the precise condition under which the fractional quantum Hall phases can be stabilized. It is now understood that the key to obtaining the fractional quantum Hall phases is the energy band whose eigenstates are holomorphic functions in both real and momentum space coordinates. Landau levels are indeed examples of such energy bands with an additional special property of having flat geometrical features. In this paper, we prove that, in fact, the only energy eigenstates having holomorphic wave functions with a flat geometry are the Landau levels and their higher Chern number analogs. Since it has been known that any holomorphic eigenstates can be constructed from the ones with a flat geometry such as the Landau levels, our uniqueness proof of the Landau levels allows one to construct any possible holomorphic eigenstate with which the fractional quantum Hall phases can be stabilized.

Solving partial differential equations for extremely large-scale systems within a feasible computation time serves in accelerating engineering developments. Quantum computing algorithms, particularly the Hamiltonian simulations, present a potential and promising approach to achieve this purpose. Actually, there are several oracle-based Hamiltonian simulations with potential quantum speedup, but their detailed implementations and accordingly the detailed computational complexities are all unclear. This paper presents a method that enables us to explicitly implement the quantum circuit for Hamiltonian simulation; the key technique is the explicit gate construction of differential operators contained in the target partial differential equation discretized by the finite difference method. Moreover, we show that the space and time complexities of the constructed circuit are exponentially smaller than those of conventional classical algorithms. We also provide numerical experiments and an experiment on a real device for the wave equation to demonstrate the validity of our proposed method.

In this paper, we propose a method for denoising experimental density matrices that combines standard quantum state tomography with an attention-based neural network architecture. The algorithm learns the noise from the data itself, without a priori knowledge of its sources. Firstly, we show how the proposed protocol can improve the averaged fidelity of reconstruction over linear inversion and maximum likelihood estimation in the finite-statistics regime, reducing at least by an order of magnitude the amount of necessary training data. Next, we demonstrate its use for out-of-distribution data in realistic scenarios. In particular, we consider squeezed states of few spins in the presence of depolarizing noise and measurement/calibration errors and certify its metrologically useful entanglement content. The protocol introduced here targets experiments involving few degrees of freedom and afflicted by a significant amount of unspecified noise. These include NISQ devices and platforms such as trapped ions or photonic qudits.

In computer and system sciences, higher-order cellular automata (HOCA) are a type of cellular automata that evolve over multiple time steps and generate complex patterns, which have various applications, such as secret-sharing schemes, data compression, and image encryption. In this paper, we introduce HOCA to quantum many-body physics and construct a series of symmetry-protected topological (SPT) phases of matter, in which symmetries are supported on a great variety of subsystems embbeded in the SPT bulk. We call these phases HOCA-generated SPT (HGSPT) phases. Specifically, we show that HOCA can generate not only well-understood SPTs with symmetries supported on either regular (e.g., linelike subsystems in the two-dimensional cluster model) or fractal subsystems, but also a large class of unexplored SPTs with symmetries supported on more choices of subsystems. One example is mixed-subsystem SPT that has either fractal and linelike subsystem symmetries simultaneously or two distinct types of fractal symmetries simultaneously. Another example is chaotic-subsystem SPT in which chaotic-looking symmetries are significantly different from and thus cannot reduce to fractal or regular subsystem symmetries. We also introduce a new notation system to characterize HGSPTs. We prove that all possible subsystem symmetries in a square lattice can be locally simulated by an HOCA-generated symmetry. As the usual two-point strange correlators are trivial in most HGSPTs, we find that the nontrivial SPT orders can be detected by what we call multi point strange correlators. We propose a universal procedure to design the spatial configuration of the multi point strange correlators for a given HGSPT phase. Specifically, we find deep connections between multi point strange correlators and the spurious topological entanglement entropy (STEE), both exhibiting long-range behavior in a short-range entangled state. Our HOCA approaches and multi point strange correlators pave the way for a unified paradigm to design, classify, and detect phases of matter with symmetries supported on a great variety of subsystems, and also provide potential useful perspective in surpassing the computational irreducibility of HOCA in a quantum mechanical way.

Accurate quantum computing relies on the precision of quantum gates. However, quantum gates in practice are generally affected by dissipative environments, which can significantly reduce their fidelity. In this paper, we elucidate the fundamental relations between the average fidelity of generic quantum gates and the dissipation that occurs during the computing processes. Considering scenarios in which a quantum gate is subject to Markovian environments, we rigorously derive fidelity-dissipation relations that hold for arbitrary operational times. Intriguingly, when the quantum gate undergoes thermal relaxation, the result can be used as a valuable tool for estimating dissipation through experimentally measurable fidelity, without requiring detailed knowledge of the dissipative structure. For the case of arbitrary environments, we uncover a trade-off relation between the average fidelity and energy dissipation, implying that these quantities cannot be large simultaneously. Our results unveil the computational limitations imposed by thermodynamics, shedding light on the profound connection between thermodynamics and quantum computing.

Characterization of noise in current near-term quantum devices is of paramount importance to fully use their computational power. However, direct quantum process tomography becomes unfeasible for systems composed of tens of qubits. A promising alternative method based on tensor networks was recently proposed [Nat. Commun. 14, 2858 (2023)2041-172310.1038/s41467-023-38332-9]. In this paper, we adapt it for the characterization of noise channels on near-term quantum computers and investigate its performance thoroughly. In particular, we show how experimentally feasible tomographic samples are sufficient to accurately characterize realistic correlated noise models affecting individual layers of quantum circuits, and study its performance on systems composed of up to 20 qubits. Furthermore, we combine this noise characterization method with a recently proposed noise-aware tensor network error mitigation protocol for correcting outcomes in noisy circuits, resulting accurate estimations even on deep circuit instances. This positions the tensor-network-based noise characterization protocol as a valuable tool for practical error characterization and mitigation in the near-term quantum computing era.

What are the fundamental limits and advantages of using a catalyst to aid thermodynamic transformations between quantum systems? In this paper, we answer this question by focusing on transformations between energy-incoherent states under the most general energy-conserving interactions among the system, the catalyst, and a thermal environment. The sole constraint is that the catalyst must return unperturbed and uncorrelated with the other subsystems. More precisely, we first upper bound the set of states to which a given initial state can thermodynamically evolve (the catalyzable future) or from which it can evolve (the catalyzable past) with the help of a strict catalyst. Secondly, we derive lower bounds on the dimensionality required for the existence of catalysts under thermal process, along with bounds on the catalyst's state preparation. Finally, we quantify the catalytic advantage in terms of the volume of the catalyzable future and demonstrate its utility in an exemplary task of generating entanglement and cooling a quantum system using thermal resources.