Twelve-qubit quantum computing for chemistry
Accurate electronic structure calculations are considered one of the most anticipated applications of quantum computing that will revolutionize ...theoretical chemistry and other related fields. Using the Google Sycamore quantum processor, Google AI Quantum and collaborators performed a variational quantum eigensolver (VQE) simulation of two intermediate-scale chemistry problems: the binding energy of hydrogen chains (as large as H
12
) and the isomerization mechanism of diazene (see the Perspective by Yuan). The simulations were performed on up to 12 qubits, involving up to 72 two-qubit gates, and show that it is possible to achieve chemical accuracy when VQE is combined with error mitigation strategies. The key building blocks of the proposed VQE algorithm are potentially scalable to larger systems that cannot be simulated classically.
Science
, this issue p.
1084
; see also p.
1054
Accurate quantum simulations of chemistry are performed using up to 12 superconducting qubits and 72 two-qubit gates.
The simulation of fermionic systems is among the most anticipated applications of quantum computing. We performed several quantum simulations of chemistry with up to one dozen qubits, including modeling the isomerization mechanism of diazene. We also demonstrated error-mitigation strategies based on
N
-representability that dramatically improve the effective fidelity of our experiments. Our parameterized ansatz circuits realized the Givens rotation approach to noninteracting fermion evolution, which we variationally optimized to prepare the Hartree-Fock wave function. This ubiquitous algorithmic primitive is classically tractable to simulate yet still generates highly entangled states over the computational basis, which allowed us to assess the performance of our hardware and establish a foundation for scaling up correlated quantum chemistry simulations.
Faster algorithms for combinatorial optimization could prove transformative for diverse areas such as logistics, finance and machine learning. Accordingly, the possibility of quantum enhanced ...optimization has driven much interest in quantum technologies. Here we demonstrate the application of the Google Sycamore superconducting qubit quantum processor to combinatorial optimization problems with the quantum approximate optimization algorithm (QAOA). Like past QAOA experiments, we study performance for problems defined on the planar connectivity graph native to our hardware; however, we also apply the QAOA to the Sherrington–Kirkpatrick model and MaxCut, non-native problems that require extensive compilation to implement. For hardware-native problems, which are classically efficient to solve on average, we obtain an approximation ratio that is independent of problem size and observe that performance increases with circuit depth. For problems requiring compilation, performance decreases with problem size. Circuits involving several thousand gates still present an advantage over random guessing but not over some efficient classical algorithms. Our results suggest that it will be challenging to scale near-term implementations of the QAOA for problems on non-native graphs. As these graphs are closer to real-world instances, we suggest more emphasis should be placed on such problems when using the QAOA to benchmark quantum processors.It is hoped that quantum computers may be faster than classical ones at solving optimization problems. Here the authors implement a quantum optimization algorithm over 23 qubits but find more limited performance when an optimization problem structure does not match the underlying hardware.
Quantum many-body systems display rich phase structure in their low-temperature equilibrium states
. However, much of nature is not in thermal equilibrium. Remarkably, it was recently predicted that ...out-of-equilibrium systems can exhibit novel dynamical phases
that may otherwise be forbidden by equilibrium thermodynamics, a paradigmatic example being the discrete time crystal (DTC)
. Concretely, dynamical phases can be defined in periodically driven many-body-localized (MBL) systems via the concept of eigenstate order
. In eigenstate-ordered MBL phases, the entire many-body spectrum exhibits quantum correlations and long-range order, with characteristic signatures in late-time dynamics from all initial states. It is, however, challenging to experimentally distinguish such stable phases from transient phenomena, or from regimes in which the dynamics of a few select states can mask typical behaviour. Here we implement tunable controlled-phase (CPHASE) gates on an array of superconducting qubits to experimentally observe an MBL-DTC and demonstrate its characteristic spatiotemporal response for generic initial states
. Our work employs a time-reversal protocol to quantify the impact of external decoherence, and leverages quantum typicality to circumvent the exponential cost of densely sampling the eigenspectrum. Furthermore, we locate the phase transition out of the DTC with an experimental finite-size analysis. These results establish a scalable approach to studying non-equilibrium phases of matter on quantum processors.
Information scrambling in quantum circuits Mi, Xiao; Roushan, Pedram; Quintana, Chris ...
Science (American Association for the Advancement of Science),
2021-Dec-17, 2021-12-17, 20211217, Letnik:
374, Številka:
6574
Journal Article
Recenzirano
Odprti dostop
Interactions in quantum systems can spread initially localized quantum information into the exponentially many degrees of freedom of the entire system. Understanding this process, known as quantum ...scrambling, is key to resolving several open questions in physics. Here, by measuring the time-dependent evolution and fluctuation of out-of-time-order correlators, we experimentally investigate the dynamics of quantum scrambling on a 53-qubit quantum processor. We engineer quantum circuits that distinguish operator spreading and operator entanglement and experimentally observe their respective signatures. We show that whereas operator spreading is captured by an efficient classical model, operator entanglement in idealized circuits requires exponentially scaled computational resources to simulate. These results open the path to studying complex and practically relevant physical observables with near-term quantum processors.
Increases in concentrations of greenhouse gases projected for the 21st century are expected to lead to increased mean global air and ocean temperatures. The National Assessment of Potential ...Consequences of Climate Variability and Change (NAST 2001) was based on a series of regional and sector assessments. This paper is a summary of the coastal and marine resources sector review of potential impacts on shorelines, estuaries, coastal wetlands, coral reefs, and ocean margin ecosystems. The assessment considered the impacts of several key drivers of climate change: sea level change; alterations in precipitation patterns and subsequent delivery of freshwater, nutrients, and sediment; increased ocean temperature; alterations in circulation patterns; changes in frequency and intensity of coastal storms; and increased levels of atmospheric CO sub(2). Increasing rates of sea-level rise and intensity and frequency of coastal storms and hurricanes over the next decades will increase threats to shorelines, wetlands, and coastal development. Estuarine productivity will change in response to alteration in the timing and amount of freshwater, nutrients, and sediment delivery. Higher water temperatures and changes in freshwater delivery will alter estuarine stratification, residence time, and eutrophication. Increased ocean temperatures are expected to increase coral bleaching and higher CO sub(2) levels may reduce coral calcification, making it more difficult for corals to recover from other disturbances, and inhibiting poleward shifts. Ocean warming is expected to cause poleward shifts in the ranges of many other organisms, including commercial species, and these shifts may have secondary effects on their predators and prey. Although these potential impacts of climate change and variability will vary from system to system, it is important to recognize that they will be superimposed upon, and in many cases intensify, other ecosystem stresses (pollution, harvesting, habitat destruction, invasive species, land and resource use, extreme natural events), which may lead to more significant consequences.
The field of theranostics is rapidly advancing, driven by the goals of enhancing patient care. Recent breakthroughs in artificial intelligence (AI) and its innovative theranostic applications have ...marked a critical step forward in nuclear medicine, leading to a significant paradigm shift in precision oncology. For instance, AI-assisted tumor characterization, including automated image interpretation, tumor segmentation, feature identification, and prediction of high-risk lesions, improves diagnostic processes, offering a precise and detailed evaluation. With a comprehensive assessment tailored to an individual's unique clinical profile, AI algorithms promise to enhance patient risk classification, thereby benefiting the alignment of patient needs with the most appropriate treatment plans. By uncovering potential factors unseeable to the human eye, such as intrinsic variations in tumor radiosensitivity or molecular profile, AI software has the potential to revolutionize the prediction of response heterogeneity. For accurate and efficient dosimetry calculations, AI technology offers significant advantages by providing customized phantoms and streamlining complex mathematical algorithms, making personalized dosimetry feasible and accessible in busy clinical settings. AI tools have the potential to be leveraged to predict and mitigate treatment-related adverse events, allowing early interventions. Additionally, generative AI can be utilized to find new targets for developing novel radiopharmaceuticals and facilitate drug discovery. However, while there is immense potential and notable interest in the role of AI in theranostics, these technologies do not lack limitations and challenges. There remains still much to be explored and understood. In this study, we investigate the current applications of AI in theranostics and seek to broaden the horizons for future research and innovation.
Multiple nerve transfer techniques are used to treat patients with nerve injuries when a primary repair is not possible. These techniques are categorized to end-to-end, end-to-side, and side-to-side ...neurorrhaphy. Our study aims to explore the utility of the cross-bridge ladder technique (H-shaped), which has shown promising results in animal models and probably underutilized clinically.
Four patients with significant loss of ankle dorsiflexion were seen in the clinic and underwent evaluation, including electrodiagnostic studies. A cross-bridge ladder repair technique was used between the tibial nerve as the donor and the common peroneal nerve as the recipient via one or two nerve grafts coapted in parallel with end-to-side neurorrhaphies. Dorsiflexion strength was measured preoperatively using the Medical Research Council (MRC) grading system and at each postoperative follow-up appointment.
All four patients had suffered persistent and severe foot drop (MRC of 0) following trauma that had occurred between 6 and 15 months preoperatively. Three of the four patients improved to an MRC of 2 several months postoperatively. The last patient had an immediate improvement to an MRC of 2 by his first month and had a complete recovery of ankle dorsiflexion within 4 months from surgery.
We demonstrate the utility and clinical outcomes of the cross-bridge ladder technique in patients with persistent and prolonged foot drop following trauma. Both early and late recovery were seen while all patients regained motor function, with some patients continuing to improve up to the most recent follow-up. IRB Approval: Obtained 2013-1411-CP005.
Combination of CDF and D0 W -Boson mass measurements Agnew, J. P.; Annovi, A.; Bandurin, D. V. ...
Physical review. D, Particles, fields, gravitation, and cosmology,
09/2013, Letnik:
88, Številka:
5
Journal Article
Recenzirano
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We summarize and combine direct measurements of the mass of the W boson in radicals = 1.96 TeV proton-antiproton collision data collected by CDF and D0 experiments at the Fermilab Tevatron Collider. ...Earlier measurements from CDF and D0 are combined with the two latest, more precise measurements: a CDF measurement in the electron and muon channels using data corresponding to 2.2 fb super(-1) of integrated luminosity, and a D0 measurement in the electron channel using data corresponding to 4.3 fb super(-1) of integrated luminosity. The resulting Tevatron average for the mass of the W boson is MW = 80387 + or - 16 MeV. Including measurements obtained in electron-positron collisions at LEP yields the most precise value of MW = 80385 + or - 15 MeV.
We combine six measurements of the inclusive top-quark pair (tt) production cross section (sigmatt) from data collected with the CDF and DO detectors at the Fermilab Tevatron with proton-antiproton ...collisions at radicals = 1.96 TeV. The data correspond to integrated luminosities of up to 8.8 fb super(-1). We obtain a value of sigmatt = 7.60 + or - 0.41 pb for a top-quark mass of mt = 172.5 GeV. The contributions to the uncertainty are 0.20 pb from statistical sources, 0.29 pb from systematic sources, and 0.21 pb from the uncertainty on the integrated luminosity. The result is in good agreement with the standard model expectation of (ProQuest: Formulae and/or non-USASCII text omitted) pb at next-to-next-to-leading order and next-to-next-to leading logarithms in perturbative QCD.
Abstract
Early detection of Adenocarcinoma of the Pancreas (ACP) is critical to improving outcomes. Since the development of ACP is thought to begin a couple decades prior to clinical presentation, ...the possibility exists that evolving changes in the pancreas gland (PG) may already be present on historical standard of care (h-SOC) CT scans obtained years earlier in patients who present for other indications. Advanced image analysis using quantitative texture analysis (QTA) techniques can detect subtle changes in tissue/tumors composition (including fat) and may be useful in tumor detection, diagnosis and response assessments. We hypothesized that changes in tissue texture are detectable on h-SOC in patients who subsequently develop ACP and, if identified, would contribute significantly towards the development of tools to aid in identifying tissue at risk for ACP An IRB-exempt, retrospective, single institution study of 27 matched h-SOC and ACP diagnostic CTs from a single institution was performed. Subjects who had ACP and h-SOC CTs between 3-15 years prior were included. Deidentified scans were transferred to the imaging core lab for QTA and fat fraction (FF) analysis. The pancreas gland (PG) was divided into 7 regions (uncinate, head, neck-genu, body prox,mid,dis and tail) for volumes-of interest (VOIs) placement on the h-SOC portal venous phase axial images. A single radiologist verified VOI placement, confirmed the lack of ACP on h-SOC images and was blinded to the location of subsequent ACP development. First order QTA histogram frequency curves derivatives (mean, SD, skewness, kurtosis, mean positive Pixel (MPP), at each cluster SSF setting from 0-6mm) were recorded along with FF. Inferential statistical analysis was performed to identify QTA/FF differences between PG regions that subsequently developed ACP from those that did not (p <0.05 significance). A total of 22/27 subjects (81%) had suitable portal venous phase CTs for QTA while evaluable FF data was available for all subjects. ACP developed in PG head in 45% of subjects. The average time from h-SOC to diagnostic ACP scan was 7.6 years (range, 3.9 years-13.9 years). QTA results showed a difference in tissue texture (QTAskewness > -0.480) in PG regions that subsequently developed ACP compared to regions that did not (T-statistics= -2.148; AUCROC= 0.625 p=.038). There was also a > 3-fold increase in PG tail fat in subjects that developed tail ACP (t-statistics= -3.048; p = 0.002; AUCROC= 0.819 p=.023). LOGR models showed that PG regions that subsequently developed ACP had differences in QTA mean, skewness, kurtosis and total FF on h-SOC scans compared to normal PG tissue (LL ratio-p=.004, pseudo R2=.104). Tissue texture and fat composition differences in regions of the PG may be present on h-SOC CT scans several years prior to clinical manifestation of ACP. If validated, tissue at risk could be identified well in advance of actual ACP development allowing for new opportunities for PAC interception. The investigators acknowledge the Marley Foundation for their generous support.
Citation Format: Ronald L. Korn, Daniel D. Von Hoff, Andre Burkett, Dominic Zygadlo, Taylor Brodie, Kathleen Panak, Sweta Rajan, Derek Cridebring, Michael J. Demeure. Detection of early tissue changes on historical CT scans in the regions of the pancreas gland that subsequently develop adenocarcinoma using quantitative textural analysis and fat fraction analysis abstract. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-010.
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