8 research outputs found
Fast and reliable entanglement distribution with quantum repeaters: principles for improving protocols using reinforcement learning
Future quantum technologies such as quantum communication, quantum sensing,
and distributed quantum computation, will rely on networks of shared
entanglement between spatially separated nodes. In this work, we provide
improved protocols/policies for entanglement distribution along a linear chain
of nodes, both homogeneous and inhomogeneous, that take practical limitations
such as photon losses, non-ideal measurements, and quantum memories with short
coherence times into account. For a wide range of parameters, our policies
improve upon previously known policies, such as the
``swap-as-soon-as-possible'' policy, with respect to both the waiting time and
the fidelity of the end-to-end entanglement. This improvement is greatest for
the most practically relevant cases, namely, for short coherence times, high
link losses, and highly asymmetric links. To obtain our results, we model
entanglement distribution using a Markov decision process, and then we use the
Q-learning reinforcement learning (RL) algorithm to discover new policies.
These new policies are characterized by dynamic, state-dependent memory cutoffs
and collaboration between the nodes. In particular, we quantify this
collaboration between the nodes. Our quantifiers tell us how much ``global''
knowledge of the network every node has. Finally, our understanding of the
performance of large quantum networks is currently limited by the computational
inefficiency of simulating them using RL or other optimization methods. Thus,
in this work, we present a method for nesting policies in order to obtain
policies for large repeater chains. By nesting our RL-based policies for small
repeater chains, we obtain policies for large repeater chains that improve upon
the swap-as-soon-as-possible policy, and thus we pave the way for a scalable
method for obtaining policies for long-distance entanglement distribution.Comment: Version 2, title changed, some typos fixed. 27 pages, 18 figures and
3 tables. Comments are welcom
Noisy Coherent Population Trapping: Applications to Noise Estimation and Qubit State Preparation
Coherent population trapping is a well-known quantum phenomenon in a driven
system, with many applications across quantum optics. However, when a
stochastic bath is present in addition to vacuum noise, the observed trapping
is no longer perfect. Here we derive a time-convolutionless master equation
describing the equilibration of the system in the presence of
additional temporally correlated classical noise, with an unknown decay
parameter. Our simulations show a one-to-one correspondence between the decay
parameter and the depth of the characteristic dip in the photoluminescence
spectrum, thereby enabling the unknown parameter to be estimated from the
observed spectra. We apply our analysis to the problem of qubit state
initialization in a system via dark states and show how the
stochastic bath affects the fidelity of such initialization as a function of
the desired dark-state amplitudes. We show that an optimum choice of Rabi
frequencies is possible
The performance of random bosonic rotation codes
Bosonic error correcting codes utilize the infinite dimensional Hilbert space
of a harmonic oscillator to encode a qubit. Bosonic rotation codes are
characterized by a discrete rotation symmetry in their Wigner functions and
include codes such as the cat and binomial codes.We define two different
notions of random bosonic rotation codes and numerically explore their
performance against loss and dephasing. We find that the best random rotation
codes can outperform cat and binomial codes in a certain parameter regime where
loss is large and dephasing errors are small.Comment: 9 Pages, 9 Figs, Reuploaded to fix incorrect figure generatio
Low-Light Shadow Imaging using Quantum-Noise Detection with a Camera
We experimentally demonstrate an imaging technique based on quantum noise
modification after interaction with an opaque object. By using a homodyne-like
detection scheme, we eliminate the detrimental effect of the camera's dark
noise, making this approach particularly attractive for imaging scenarios that
require weak illumination. Here, we reconstruct the image of an object
illuminated with a squeezed vacuum using a total of 800 photons, utilizing less
than one photon per frame on average
Wave-front reconstruction via single-pixel homodyne imaging
We combine single-pixel imaging and homodyne detection to perform full object recovery (phase and amplitude). Our method does not require any prior information about the object or the illuminating fields. As a demonstration, we reconstruct the optical properties of several semi-transparent objects and find that the reconstructed complex transmission has a phase precision of 0.02 radians and a relative amplitude precision of 0.01.
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Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.
Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (nâ=â143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (nâ=â152), or no hydrocortisone (nâ=â108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (nâ=â137), shock-dependent (nâ=â146), and no (nâ=â101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707
Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19
IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19.
Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19.
DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 nonâcritically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022).
INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (nâ=â257), ARB (nâ=â248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; nâ=â10), or no RAS inhibitor (control; nâ=â264) for up to 10 days.
MAIN OUTCOMES AND MEASURES The primary outcome was organ supportâfree days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes.
RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ supportâfree days among critically ill patients was 10 (â1 to 16) in the ACE inhibitor group (nâ=â231), 8 (â1 to 17) in the ARB group (nâ=â217), and 12 (0 to 17) in the control group (nâ=â231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ supportâfree days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively).
CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes.
TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570
Weak Thermal State Quadrature-Noise Shadow Imaging
In this work, we theoretically and experimentally demonstrate the possibility
to create an image of an opaque object using a few-photon thermal optical
field. We utilize the Quadrature-Noise Shadow Imaging (QSI) technique that
detects the changes in the quadrature-noise statistics of the probe beam after
its interaction with an object. We show that such thermal QSI scheme has an
advantage over the classical differential imaging when the effect of dark
counts is considered. At the same time, the easy availability of thermal
sources for any wavelength makes the method practical for broad range of
applications, not accessible with, e.g. quantum squeezed light. As a proof of
principle, we implement this scheme by two distinct methods: first, with
pseudo-thermal light generated by rotating ground glass (RGG) method and
second, with thermal beam generated by Four-Wave Mixing (FWM) method. The RGG
method shows simplicity and robustness of QSI scheme while the FWM method
validates theoretical signal-to-noise ratio predictions. Finally, we
demonstrate low-light imaging abilities with QSI by imaging a biological
specimen on a CCD camera, detecting just 0.006 photons per pixel on average.Comment: 9 pages, 8 figure