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Optimal Detection of Rotations about Unknown Axes by Coherent and Anticoherent States




John Martin1, Stefan Weigert2, and Olivier Giraud3

1Institut de Physique Nucléaire, Atomique et de Spectroscopie, CESAM, University of Liège, B-4000 Liège, Belgium
2Department of Mathematics, University of York, UK-York YO10 5DD, United Kingdom
3Université Paris-Saclay, CNRS, LPTMS, 91405 Orsay, France

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Coherent and anticoherent states of spin systems up to spin $j=2$ are known to be optimal in order to detect rotations by a known angle but unknown rotation axis. These optimal quantum rotosensors are characterized by minimal fidelity, given by the overlap of a state before and after a rotation, averaged over all directions in space. We calculate a closed-form expression for the average fidelity in terms of anticoherent measures, valid for arbitrary values of the quantum number $j$. We identify optimal rotosensors (i) for arbitrary rotation angles in the case of spin quantum numbers up to $j=7/2$ and (ii) for small rotation angles in the case of spin quantum numbers up to $j=5$. The closed-form expression we derive allows us to explain the central role of anticoherence measures in the problem of optimal detection of rotation angles for arbitrary values of $j$.

Advances in measurement techniques have often led to progress in physics. Over time, metrology developed as a subject of its own, especially in the context of defining standard units for physical quantities. Quantum theory provides new perspectives on measurements but also new challenges. The currently emerging quantum technologies require ever better control of microscopic systems and, hence, measurements which are as accurate as possible. In this paper, we are interested to determine whether a quantum system has undergone a rotation by a known angle about an unknown axis. The states optimally suited for this task are called “optimal quantum rotosensors”. They are characterized by minimal fidelity, given by the overlap of a state before and after a rotation, averaged over all directions in space. The closed-form expression we derive for the fidelity and numerical computations allow us to explain the central role of a specific class of quantum states in this problem which are known as “anticoherent” states.

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Could not fetch Crossref cited-by data during last attempt 2020-06-22 15:53:37: Could not fetch cited-by data for 10.22331/q-2020-06-22-285 from Crossref. This is normal if the DOI was registered recently. On SAO/NASA ADS no data on citing works was found (last attempt 2020-06-22 15:53:38).



Accelerating egg yolks shed light on brain injuries




Egg yolk and white
Brain food: a raw chicken egg within its membrane, with the shell removed. The yellow yolk floating within the white is visible. (Courtesy: Biswarup Ganguly/CC BY 3.0)

New insights into how brain injuries occur have been gleaned from a simple study of how an egg yolk is deformed when rotational forces are applied to its outer shell. The experiments were done by Ji Lang, Rungun Nathan and Qianhong Wu at Villanova University in the US, who conclude that brain injuries are far more likely to result from rotational impacts on the skull than from direct translational impacts. Their work provides new insights into how soft matter behaves and could lead to a better understanding of how certain sports injuries occur.

In living organisms, it is common to find highly deformable soft matter that is bathed in a liquid and enclosed in a rigid container. A familiar example is the human brain, which is surrounded by a thin layer of cerebrospinal fluid and encased in a hard skull. It is now widely believed that sudden translational and rotational impacts on the skull will temporarily deform the soft brain, potentially causing serious injury as intricate networks of neurons are disrupted. To study these impacts in further detail, Wu’s team exploited the similarities between the brain with a simpler system: a soft egg yolk surrounded by fluid white and encased in a hard eggshell.

Past studies have explored how soft matter deforms in response to rapidly changing shear and spinning forces in surrounding fluids. Wu and colleagues extended this research by looking at how egg yolks deform during non-destructive translational and rotational impacts on their outer shells. To do this, they devised a simple experiment involving a kitchen gadget that scrambles an egg in its shell. This allowed the team to subject yolks to a variety of shear and spinning flows and image their deformation over time.

Expanding yolk

The images revealed that the yolks only deformed slightly in response to translational impacts but were highly sensitive to rotational impacts – particularly those involving deceleration. In this case, the researchers determined that the fluid pressure outside the yolk initially becomes larger than the centrifugal force of the fluid enclosed by its delicate membrane, leading to compression at the centre of the yolk. However, if the outer shell’s rotation suddenly stops, these centrifugal forces will become far greater than the outside pressure. This means the yolk will no longer hold its shape and will expand into the surrounding fluid.

The team’s results offer new insights into why brain injuries appear to be more likely to occur after certain types of impact, particularly in sports. Here, rapid rotational decelerations can occur in situations ranging from a boxer’s uppercut to the chin, to impacts on irregularly shaped helmets, like those used in ice hockey. The research may also inform future studies of membrane-enclosed soft matter, including red blood cells and spinning droplets.

The research is described in Physics of Fluids.


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MR-Linac verification with RadCalc




Join the audience for a live webinar at 7 p.m. GMT/1 p.m. CDT on 23 February 2021 exploring how RadCalc can improve accuracy, efficiency, and safety in the QA process for MR-Linacs Unity and ViewRay

Want to take part in this webinar?

Participants to this webinar will learn how RadCalc can improve accuracy, efficiency, and safety in the QA process for MR-Linacs Unity and ViewRay.

Hosted by Kathie Carrington, you will:

  • Learn about the automated workflow of RadCalc.
  • Find out more about the use of RadCalc verifying MR.
  • Take part in a question and answer session.

Want to take part in this webinar?

Kathie Carrington is director of applications and training at LifeLine Software, Inc. Company of LAP Group. She has more than 25 years of radiation oncology experience, having held positions from radiation therapist, dosimetrist and department director. She joined Lifeline Software in 2012 and has been connecting radiation therapy departments with software that increases productivity and safety ever since.


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CAR-T cells turned into molecular computers destroy tumours more effectively




et al Cell Systems 10.1016/j.cels.2020.08.002, ©2020, with permission from Elsevier)”>et al Cell Systems 10.1016/j.cels.2020.08.002, ©2020, with permission from Elsevier)”>

One of the biggest challenges in cancer therapy is to develop drugs that are as selective as possible, so as to target cancer cells while leaving healthy surrounding tissues intact. Over the last decade, the development of chimeric antigen receptor (CAR) T cell-based immunotherapies has brought us significantly closer to solving this challenge. These therapies involve collecting from a patient’s blood the immune system T cells responsible for identifying and killing cancer cells, and engineering them to produce new surface proteins (CAR) that recognise specific markers – antigens – on the tumours. Once reinjected into the patient’s bloodstream, these CAR-T cells can identify and attack cancer cells more effectively.

While CAR-T cells have proved efficient for treating blood cancers such as leukaemia and lymphoma, solid tumours, such as found in the breast, liver or lung, have been more difficult to vanquish. Many of the markers characteristic to those tumours are also found in normal tissues, causing the destruction of both, as CAR-T cells do not distinguish between healthy and diseased cells. The challenge has hence shifted from “how do we target cancer cells” to “how do we do this while ensuring healthy tissues are left unharmed”.

A possible approach has recently been presented in two complementary articles by Wendell Lim’s research group at University of California San Francisco and Olga Troyanskaya’s group at Princeton and the Flatiron Institute of the Simons Foundation. The researchers combine machine learning and cell engineering techniques to create CAR-T cells that, instead of recognising just one antigen, use Boolean logic (AND, OR and NOT operators) to target combinations of up to three antigens. For example, if antigens A and B are mostly found in tumours but can also be present in healthy cells, while C is only found in normal tissues, the combination “A” OR “B” AND NOT “C” would help differentiate the tumour from normal tissues.

“Currently, most cancer treatments, including cell therapies, are told ‘block this’ or ‘kill this’,” explains Lim. “We want to increase the nuance and sophistication of the decisions that a therapeutic cell makes.”

Preventing off-target killing of healthy cells

In the first article, published in Cell Systems, the researchers investigated the efficiency of antigen combinations to distinguish normal and cancerous tissues in a database of the human genome containing 2358 antigens. A clustering-based score sorted over 2.5 million antigen pairs and approximately 60 million triple antigens. Pairing antigens using either AND or NOT logic gates significantly improved tumour recognition, outperforming well-established single antigens already investigated clinically, in 33 tumours and 34 normal samples.

These Boolean instructions can be programmed into CAR-T cells via synthetic Notch receptors (synNotch), one of the latest developments in cell engineering. Briefly, when a protein binds the Notch receptor, a portion of the receptor breaks off and heads for the cell nucleus, where it acts as a switch to turn on other genes. This allows cells to behave like molecular computers that can sense their environment and then integrate that information to make decisions.

To prove the accuracy of the method, the researchers programmed synNotch receptors to recognise two markers found in kidney tumours, CD70 and AXL, using an AND gate. Targeted separately, CAR-T cells would result in off-target damage, as CD70 is also widely present in healthy blood cells and AXL can be found in healthy lung tissues. But targeting both using an AND gate not only suppressed their expression in tumours in vitro, it also ensured that normal tissue containing just one of these antigens were left unharmed. For example, Raji B cells, which are found in the blood and express CD70, had a survival rate close to 100% with the two antigens, while only around 20% survived when only CD70 was targeted.

Adding a third antigen in the combination helped improve the overall performance across several types of tumour. It also revealed the importance of NOT gates, with 92 of the top-100 combinations of gates for each cancer having at least one such gate. This further highlights the importance of NOT gates in preventing toxic cross reactions, while also significantly improving the correct identification of challenging tumours, such as cholangiocarcinoma, a type of cancer that forms in bile ducts.

New killing strategies

In a second study, published in Science, Lim’s research team expanded on their initial work and daisy-chained multiple synNotch receptors to create a host of complex cancer recognition circuits. The “plug-and-play” nature of synNotch enabled them to customize circuits with diverse Boolean functions, allowing for precise recognition of diseased cells and a range of responses when those cells are identified.

Such circuits can be used in complex scenarios. For example, an antigen localized on the surface of a cell can be targeted, and the decision whether or not to launch the killing process would then be tied to the presence of a second cancer antigen inside the cell. Since CAR-T cells are usually restricted to recognising extracellular antigens, which only represent about 25% of a cell proteome, resorting to this Boolean logic enables targeting of new cancer antigens. As the researchers demonstrated in vitro with melanoma cells, this dual intracellular–extracellular targeting approach both improved specificity and reduced off-target killing.

In vivo experiments also showed promising results. The researchers injected a mouse presenting different tumours in each flank – one with two antigens, one with the same two antigens plus an additional third – with a three-antigen-AND-gate T cell composed of three sequentially linked receptors. Allowed to autonomously explore and act on both tumours, the T cells rapidly cleared the three-antigen tumours while ignoring the two-antigen tumours on the opposing flank, similarly to the results observed in vitro.

The possibilities are endless as these smart cells can be designed to fight all kind of tumours. Lim’s group is now exploring how these circuits could be used in CAR-T cells to treat glioblastoma, an aggressive form of brain cancer that is nearly always fatal, using conventional therapies.

“You’re not just looking for one magic-bullet target. You’re trying to use all the data,” Lim says. “We need to comb through all of the available cancer data to find unambiguous combinatorial signatures of cancer. If we can do this, then it could launch the use of these smarter cells that really harness the computational sophistication of biology and have real impact on fighting cancer.”


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Joe Biden’s inauguration: why the rebuilding of trust in science is not over yet




Taken from the January 2021 issue of Physics World, where it appeared under the headline “Not over yet”.. Members of the Institute of Physics can enjoy the full issue via the Physics World app.

The inauguration of Joe Biden as the 46th US President doesn’t necessarily herald a new day for science, cautions Robert P Crease

Biden poster in NYCThe morning of Saturday 7 November 2020 was bright and sunny in Manhattan. I was working in my apartment when I heard a growing clamour outside. At first it was only shouts, but soon I heard whistles, blaring horns, and the banging of pots and pans. People began dancing in the streets and on fire escapes, and hanging out of windows. Others congregated on rooftops. An amplifier began booming Stevie Wonder’s “Signed, Sealed, Delivered”, then Three Dog Night’s ebullient “Joy to the World”. It was like a spontaneous New Year’s Eve celebration, but in the morning and without fireworks.

I knew immediately. After four uncertain days since Americans had gone to the polls, the US presidential election had just been called, thanks to the results of the vote tally from Pennsylvania. Joe Biden had clinched victory over Donald Trump (though it was still to take several weeks before he begrudgingly and gracelessly began the transition of power). Non-US citizens may not appreciate just how emotional the moment was to people such as myself, nor why the joy was so intense. A man who had, in my view, ravaged the country he was supposed to govern was heading for the exit – and not a moment too soon.

Later that evening in his victory speech, Biden mentioned science twice, referring to the need to “build on bedrock science” to help fight “the great battles of our time”, among which he included fighting the pandemic and climate change. A few moments later, vice-president-elect Kamala Harris told viewers that they had chosen “hope, unity, decency, science – and, yes, truth”. Biden, who the next day appointed eminent scientists to develop plans to cope with COVID and climate change, would replace the man who had labelled each a hoax.

Politicians can evoke science as facilely as they do the Bible. Even Donald Trump did so.

The one who all but failed to act on a virus that had affected over 15 million Americans and killed more than a quarter of a million would be replaced by one who would. Biden is to be inaugurated as the 46th US president on 20 January.

“Science returns to the White House,” said a friend.

Not so fast, I thought.

Means to an end

Politicians can evoke science as facilely as they do the Bible. Even Trump did so. After accepting the Republican nomination last summer, Donald Trump claimed that his own administration was “focusing on the science, the facts and the data” and accused his opponent Biden of not “following the science” – remarks that brought to mind my favourite anti-Trump lawn sign last year: MAKE ORWELL FICTION AGAIN. Even supposedly respectable politicians can ignore scientific findings if the science points to sufficiently unpopular actions. Imagine the reception if one of today’s politicians were to defend a plan to fight climate change by building hundreds of new nuclear-power stations because “the science” said so.

Wisely incorporating science into policies requires three abilities. First, it requires knowing how to listen. Politicians don’t read journal articles but hear voices, and scientific voices are only a tiny subset of the ones clamouring for attention. Those “following the science” know to listen differently to the voices reporting findings that have been checked and cross-checked by peers, and know how to pick out advice from advocacy. Science literacy, it is said, means the ability to choose one’s experts wisely. It’s like the discernment required when choosing a guide to take you to the top of a challenging mountain.

Trump, notoriously, lacked that discernment. Instead, he treated hearsay – and the voices inside his head – as more authoritative than those of respected scientists. He fired the head of his Climate Assessment Panel, as well as the director of the Department of Health and Human Services’ Biomedical Advanced Research and Development Authority, for voicing results that challenged own opinions. He actively sought to destroy the integrity of scientific institutions, and regarded science as a mere “special-interest” group. Over half his term elapsed before he had a science adviser.

Using science effectively requires recognizing the range of policy alternatives suggested by the findings.

Second, using science effectively requires recognizing the range of policy alternatives suggested by the findings. There are almost always more than one, and the findings are often imprecise, underdetermined or conflicting – which is most overt when models are involved, as in climate-change predictions. This is like understanding the full range of possible routes up the mountain.

Finally, there’s judging which of the possible paths you can take given your abilities, limited budgets and allies. “Politics is the art of the possible, the attainable,” as the German statesman Otto von Bismarck famously said, “the art of the next best.”

That point was brought home to me when I attended a conference on how to handle a situation that seemed intractable given the radically different and incompatible demands of scientists, politicians, administrators and community members. I remember a scientist outlining his carefully worked out approach, then concluding, “It’s the perfect solution, but it’s not implementable.” The room fell silent. Then, from the back, a voice said softly and clearly, “If it’s not implementable, it’s not a solution.” The pause reflected the participants’ discomfort with the decisive role that politics plays in such situations.

Donald Trump was unable to listen, recognize or judge, while Joe Biden seems to be able to do all three.

The critical point

Several months ago I spoke to a former science administrator of the Department of Energy (DOE) about a disastrous episode in which a valuable scientific instrument was terminated in the wake of disagreements between politicians, DOE officials, laboratory scientists and community members. I asked her what would have made things turn out better. “Trusting relationships,” she said, “between each of those parties.”

Trusting relationships provide the background that allows one to listen, recognize and judge in the first place. Such trust takes a long time to develop – and you can’t vote it in.


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