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The global race to build the world's first quantum computer has attracted enormous investment from government and industry, and it attracts a growing pool of talent. As with many cutting-edge technologies, the optimal implementation is not yet settled. This important textbook describes four of the most advanced platforms for quantum computing: nuclear magnetic resonance, quantum optics, trapped ions, and superconducting systems. The fundamental physical concepts underpinning the practical implementation of quantum computing are reviewed, followed by a balanced analysis of the strengths and weaknesses inherent to each type of hardware. The text includes more than 80 carefully designed exercises with worked solutions available to instructors, applied problems from key scenarios, and suggestions for further reading, facilitating a practical and expansive learning experience. Suitable for senior undergraduate and graduate students in physics, engineering, and computer science, Building Quantum Computers is an invaluable resource for this emerging field.
Background: Medicare claims are frequently used to study Clostridioides difficile infection (CDI) epidemiology. Categorizing CDI based on location of onset and potential exposure is critical in understanding transmission patterns and prevention strategies. While claims data are well-suited for identifying prior healthcare utilization exposures, they lack specimen collection and diagnosis dates to assign likely location of onset. Algorithms to classify CDI onset and healthcare association using claims data have been published, but the degree of misclassification is unknown. Methods: We linked patients with laboratory-confirmed CDI reported to four Emerging Infections Program (EIP) sites from 2016-2020 to Medicare beneficiaries using residence, birth date, sex, and hospitalization and/or healthcare exposure dates. Uniquely linked patients with fee-for-service Medicare A/B coverage and complete EIP case report forms were included. Patients with a claims CDI diagnosis code within ±28 days of a positive CDI test reported to EIP were categorized as hospital-onset (HO), long-term care facility onset (LTCFO), or community-onset (CO, either healthcare facility-associated [COHCFA] or community-associated [CA]) using a previously published algorithm based on claim type, ICD-10-CM code position, and duration of hospitalization (if applicable). EIP classifies CDI into these categories using positive specimen collection date and other information from chart review (e.g. admit/discharge dates). We assessed concordance of EIP and claims case classifications using Cohen’s kappa. Results: Of 10,002 eligible EIP-identified CDI cases, 7,064 were linked to a unique beneficiary; 3,451 met Medicare A/B fee-for-service coverage inclusion criteria. Of these, 650 (19%) did not have a claims diagnosis code ±28 days of the EIP specimen collection date (Table); 48% (313/650) of those without a claims diagnosis code were categorized by EIP as CA CDI. Among those with a CDI diagnosis code, concurrence of claims-based and EIP CDI classification was 68% (κ=0.56). Concurrence was highest for HO and lowest for COHCFA CDI. A substantial number of EIP-classified CO CDIs (30%, Figure) were misclassified as HO using the claims-based algorithm; half of these had a primary ICD-10 diagnosis code of sepsis (226/454; 50%). Conclusions: Evidence of CDI in claims data was found for 81% of EIP-reported CDI cases. Medicare classification algorithms concurred with the EIP classification in 68% of cases. Discordance was most common for community-onset CDI patients, many of whom were hospitalized with a primary diagnosis of sepsis. Misclassification of CO-CDI as HO may bias findings of claims-based CDI studies.
Background: Identification and timely reporting of multi-drug resistant organisms (MDROs) drives efficacy of infection prevention efforts. Data on MDRO reporting timeliness and inter-facility variability are limited. Facility-dependent variability in MDRO reporting across Tennessee was examined to identify opportunities for MDRO surveillance improvement. Methods: Data for reported Tennessee MDROs including carbapenem-resistant Enterobacterales (CRE), carbapenem-resistant Acinetobacter baumannii (CRAB), Carbapenem-resistant Pseudomonas aeruginosa (CRPA) and Candida auris, were obtained from the southeast regional Antibiotic Resistance Laboratory Network (ARLN) from 2018-2022, excluding screening and colonization specimens. Variance in days accrued from specimen collection to ARLN receipt was analyzed using one-way analysis of variance (ANOVA) with Tukey’s test (SAS 9.4). Facilities were categorized as fast (1-10 days), slow (11-20 days), or delayed (21-100 days) reporters. Results: There were 9,569 MDRO isolates reported. CRPA was reported faster than other MDROs (p < 0.001), while specimens from West Tennessee compared to other regions (p < 0.001) (Figure) and blood cultures compared to other specimens were reported more slowly (p < 0.001) (Table). There was no difference in reporting times for facilities using on-site microbiology laboratories versus reference laboratories (P = 0.062). Conclusion: MDRO reporting times varied across Tennessee by region, specimen, and organism. Future work to elucidate drivers of variability will consist of surveys and focused interviews with laboratory personnel to identify shared and unique barriers and opportunities for improvement.
Background: Infections lead to high mortality among patients on chronic dialysis; knowledge of multi-drug resistant infections is limited. The Centers for Disease Control and Prevention’s Emerging Infections Program (EIP) conducts laboratory- and population-based surveillance for carbapenem-resistant Enterobacterales (CRE) in 10 U.S. sites and carbapenem-resistant Acinetobacter baumannii (CRAB) in 9 U.S. sites. We investigated clinical characteristics, healthcare exposures, and outcomes of CRE and CRAB cases in persons on chronic dialysis from 2016-2021. Methods: Among EIP catchment-area residents on chronic dialysis, we defined a CRE case as the first isolation of Escherichia coli, Enterobacter cloacae complex, Klebsiella aerogenes (formerly Enterobacter aerogenes), Klebsiella oxytoca, Klebsiella pneumoniae, or Klebsiella variicola resistant to any carbapenem, from a normally sterile site or urine in a 30-day period. A CRAB case was defined as the first isolation of Acinetobacter baumannii complex resistant to any carbapenem (excluding ertapenem), from a normally sterile site or urine (or lower respiratory tract or wound since 2021) in a 30-day period. Medical records were reviewed. A case was considered colonized if the case culture had no associated infection type or colonization was documented in the medical record. Descriptive analyses, including analyses stratified by pathogen, were conducted. Results: Among 426 cases, 314 were CRE, and 112 were CRAB; most cases were male (235, 55.2%), Black (229, 53.8%), and 51-80 years old (320, 75.1%) (Table). An infection was associated with 363 (85.2%) case cultures; bloodstream infections (148; 40.8%), urinary tract infections (134; 36.9%), and pneumonia (17; 4.7%) were the most frequent. Overall, most cases had documented healthcare exposures (excluding outpatient dialysis) in the year before incident specimen collection, including: 366 (85.9%) hospitalizations, 235 (55.2%) surgeries, 209 (49.1%) long-term care facility stays, 54 (12.7%) long-term acute care facility stays. Additionally, 125 (29.3%) had an intensive care unit admission within the 7 days before incident specimen collection. Compared to CRE cases, a higher proportion of CRAB cases (a) had a long-term care facility stay (82/112 [73.2%] versus 127/314 [40.5%], P<.0001) or hospitalization (103/112 [92%] versus 263/314 [83.8%], P = .03) within the preceding year and (b) died within 30 days of incident specimen collection (40/112 [35.7%] versus 64/314 [20.4%], P = .001). Discussion: Among CRE and CRAB cases in persons on chronic dialysis, healthcare exposures were common, and mortality was high. Additional efforts to better describe the burden of these organisms and associated risk factors in the dialysis population are needed for tailoring infection prevention strategies to this vulnerable.
This chapter delves into the application of trapped ions in electromagnetic fields for quantum computing, starting with the technique of confining ions using a linear Paul trap. It then examines the encoding of qubits within the ions’ electronic states. The interaction between an ion and a laser, pivotal for system operations, is analyzed next. This interaction underpins the initialization of ions via laser cooling and the execution of one- and two-qubit gates. The two-qubit gates also employ the ions’ motional states to extend beyond the traditional qubit space. The process also includes a method for measuring qubit states by detecting the photons released when ions are excited. The text identifies key sources of noise that can affect ion traps. It concludes with a summary and the advantages and challenges associated with trapped-ion quantum computing.
This chapter examines the use of photon ensembles for quantum computing. It opens with a primer on photons, normal modes, and both linear and nonlinear optics. The discussion then advances to the technologies employed in generating and detecting single photons, followed by methods of qubit encoding and initialization. Subsequently, the focus shifts to qubit control, detailing the execution of single-qubit gates using linear optical elements and the Knill–Laflamme–Milburn (KLM) protocol for two-qubit gates. While the textbook predominantly centers on the circuit model, alternative models of quantum computing – specifically, one-way quantum computing and continuous-variable quantum computing – and their optical implementations are introduced. Additionally, it outlines the primary sources of noise affecting these systems. The chapter wraps up with a reflection on the comparative benefits and limitations of optical quantum computing.
This chapter delves into superconducting qubits, starting with the essentials of superconductivity and circuit design. Central to this discussion is the Josephson junction, a key element in creating superconducting qubits. The text focuses on the transmon, the archetype in this field, while acknowledging other designs. Initialization of the transmon involves sophisticated dilution refrigerators, a process that is also examined. Additionally, the principles of circuit quantum electrodynamics (QED) are introduced as the framework for qubit control and measurement. Attention is then given to noise sources and their effect on superconducting qubits, with insights that apply to various qubit systems. The chapter wraps up by highlighting the strengths and challenges of superconducting qubits for quantum computing.
Chapter 2 serves as a primer on quantum mechanics tailored for quantum computing. It reviews essential concepts such as quantum states, operators, superposition, entanglement, and the probabilistic nature of quantum measurements. This chapter focuses on two-level quantum systems (i.e. qubits). Mathematical formulations that are specific to quantum mechanics are introduced, such as Dirac (bra–ket) notation, the Bloch sphere, density matrices, and Kraus operators. This provides the reader with the necessary tools to understand quantum algorithms and the behaviour of quantum systems. The chapter concludes with a review of the quantum harmonic oscillator, a model to describe quantum systems that are complementary to qubits and used in some quantum computer implementations.
This chapter explores the origin, key components, and essential concepts of quantum computing. It begins by charting the series of discoveries by various scientists that crystallized into the idea of quantum computing. The text then examines how certain applications have driven the evolution of quantum computing from a theoretical concept to an international endeavour. Additionally, the text clarifies the distinctions between quantum and classical computers, highlighting the DiVincenzo criteria, which are the five criteria for quantum computing. It also introduces the circuit model as the foundational paradigm for quantum computation. Lastly, the chapter sheds light on the reasons for the belief that quantum computers are more powerful than classical ones (touching on quantum computational complexity) and physically realizable (touching on quantum error correction).
The third chapter examines the capabilities of liquid-state NMR systems for quantum computing. It begins by grounding the reader in the basics of spin dynamics and NMR spectroscopy, followed by a discussion on the encoding of qubits into the spin states of the nucleus of atoms inside molecules. The narrative progresses to describe the implementation of single-qubit gates via external magnetic fields, weaving in key concepts such as the rotating-wave approximation, the Rabi cycle, and pulse shaping. The technique for orchestrating two-qubit gates, leveraging the intrinsic couplings between the spins of nuclei of atoms within a molecule, is subsequently detailed. Additionally, the chapter explains the process of detecting qubits’ states through the collective nuclear magnetization of the NMR sample and outlines the steps for qubit initialization. Attention then shifts to the types of noise that affect NMR quantum computers, shedding light on decoherence and the critical T1 and T2 times. The chapter wraps up by providing a synopsis, evaluating the strengths and weaknesses of liquid-state NMR for quantum applications, and a note on the role of entanglement in quantum computing.