On Thursday, a US District Court in Oregon ordered the US government to restart the process of approving wind projects. All new wind development in the US has been on hold since August 2025, when the Department of Defense (DoD) stopped participating in a process that allows it to compel developers to alter projects in order to limit their interference with radar equipment. The court ruled, however, that the DoD's national security claims did not allow it to opt out of a process that is legally mandated.

The Trump administration has made many attempts to block wind development, both offshore and land based. Its attempts to stop offshore wind included the same approach at issue in this case: Claim that drone developments mean that radar interference by wind turbines creates a national security risk. The courts were not sympathetic to this claim, including in cases where judges examined a classified report that the DoD was using to justify blocking offshore wind construction. As a result, the administration has turned to paying companies not to pursue wind development.

In parallel, the government was pursuing a similar approach for onshore wind. Here, a law lays out a process for the DoD to evaluate any problems posed by wind turbines and negotiate changes to planned wind farms with the developers. As laid out in the new decision, the government simply stopped participating in this process in August 2025, first by refusing to sign off on previously negotiated agreements, and later by refusing to draft agreements entirely. Eventually, it simply refused to participate in negotiations at all. This has brought a halt to all wind development in the US.

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On Thursday, a US District Court in Oregon ordered the US government to restart the process of approving wind projects. All new wind development in the US has been on hold since August 2025, when the Department of Defense (DoD) stopped participating in a process that allows it to compel developers to alter projects in order to limit their interference with radar equipment. The court ruled, however, that the DoD's national security claims did not allow it to opt out of a process that is legally mandated.

The Trump administration has made many attempts to block wind development, both offshore and land based. Its attempts to stop offshore wind included the same approach at issue in this case: Claim that drone developments mean that radar interference by wind turbines creates a national security risk. The courts were not sympathetic to this claim, including in cases where judges examined a classified report that the DoD was using to justify blocking offshore wind construction. As a result, the administration has turned to paying companies not to pursue wind development.

In parallel, the government was pursuing a similar approach for onshore wind. Here, a law lays out a process for the DoD to evaluate any problems posed by wind turbines and negotiate changes to planned wind farms with the developers. As laid out in the new decision, the government simply stopped participating in this process in August 2025, first by refusing to sign off on previously negotiated agreements, and later by refusing to draft agreements entirely. Eventually, it simply refused to participate in negotiations at all. This has brought a halt to all wind development in the US.

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A lot of the AI work in biology has been focused on designing proteins. That's partly because proteins do most of the business of life, catalyzing the interesting chemistry and structuring cells. So, figuring out how to make a new protein can mean directly tinkering with biochemistry, providing new and potentially useful functions.

Since the genetic code provides a layer of abstraction between DNA and proteins, it wasn't obvious what a model trained on DNA could do. Yet people went ahead and made a large genome model, and it turned out to be able to output DNA sequences that could encode functional proteins in bacteria and mimic the gene structures found in complex cells. Now, those same models have been used to output the genomes of viruses that infect bacteria.

This isn't science fiction—all the viruses the models created are closely related to an existing virus. But they do have some distinct features that would be challenging to evolve. And the researchers who did the work, based at Stanford University, suggest we may want to start thinking now about preparing for the potential that someone could develop a related AI that can design a virus that targets vertebrates.

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D-Wave is a bit of an oddity in the quantum computing space, having been founded back in the last century. And its initial offering wasn't a quantum computer like those being developed by IBM or Google. Instead, the company built what's now called a quantum annealer, a machine that isn't general-purpose but can solve a large class of optimization problems. While the hardware shares some similarities with the qubits used in gate-based quantum computers, it operates in a fundamentally different way.

But a few years back, D-Wave started working on gate-based hardware, apparently choosing a somewhat unusual qubit technology called fluxonium. And this year, the company acquired a startup called Quantum Circuits that spun out of Yale University and has been developing what's called a dual-rail qubit (the same technology used by Amazon), which promises to make most errors very easy to detect, simplifying error correction.

On Wednesday, the company is publishing a paper in Nature that describes a key step in validating this dual-rail technology, showing that two of the qubits can be entangled without altering their best feature: Most are a single type that is easy to detect.

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When the history of our ancestry is written, the fact that we've interbred with some of our closest relatives, the Neanderthals and Denisovans, will have a central role. And it will be tempting to write it as a very tidy story: Once we got genomes from these other groups, it was possible to identify the sequences in our genomes that we shared with them.

But in reality, as scientists started poking large enough collections of data, there were regular hints of some strange ancestry in our genomes. It was hard to pin down, though, at least in part because the 2 percent on average of Neanderthal DNA found in many populations does not guarantee that any two individuals will have the same 2 percent. So having the genomes of those two groups made sense of some things researchers had already been seeing.

But knowing what we do about Neanderthal and Denisovan DNA is now allowing researchers to answer a somewhat different question: Is there anything else? Using recently developed analytical techniques, they find evidence of a third lineage that we apparently interbred with before any modern humans left Africa. Again, there were hints of this earlier, but so far, there's been no genome from a modern human relative to help us understand the details—the source of this DNA remains a "ghost lineage."

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When the history of our ancestry is written, the fact that we've interbred with some of our closest relatives, the Neanderthals and Denisovans, will have a central role. And it will be tempting to write it as a very tidy story: Once we got genomes from these other groups, it was possible to identify the sequences in our genomes that we shared with them.

But in reality, as scientists started poking large enough collections of data, there were regular hints of some strange ancestry in our genomes. It was hard to pin down, though, at least in part because the 2 percent on average of Neanderthal DNA found in many populations does not guarantee that any two individuals will have the same 2 percent. So having the genomes of those two groups made sense of some things researchers had already been seeing.

But knowing what we do about Neanderthal and Denisovan DNA is now allowing researchers to answer a somewhat different question: Is there anything else? Using recently developed analytical techniques, they find evidence of a third lineage that we apparently interbred with before any modern humans left Africa. Again, there were hints of this earlier, but so far, there has been no genome from a modern human relative to help us understand the details—the source of this DNA remains a "ghost lineage."

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There are many algorithms for which it has been mathematically proven that a quantum computer can generate results that would take a classical computer an unreasonable amount of time to generate. Unfortunately, today's quantum computers either can't run those algorithms or can only run simplified versions that classical computers can also handle. This has left the field facing a challenging question: Can we demonstrate the promise of quantum computers on today's noisy, limited hardware?

That's a more difficult question than it may first appear. If you generate a result that's out of reach of today's regular computers, it may not be possible to verify that you got the right result. And given that today's quantum computers are somewhat error-prone, getting the wrong result is a distinct possibility. Further, in the absence of a mathematical proof of the capabilities of quantum hardware, it's possible that a better classical algorithm could outperform the quantum hardware.

These issues inspired IBM to launch a quantum advantage tracker. On Thursday, the company announced three new entries that it says clearly show a quantum advantage, each using a different approach to overcoming errors and validating quantum results. "Trusted computing when you can do classical simulations is irrelevant," IBM's Jay Gambetta told Ars. "Trusted computing when you can't do classical simulations is a big deal."

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If you follow quantum computing news for long enough, it can start to seem like any quantum system that can alternate between two well-separated energy states can be used as a qubit. Atoms, ions, photons, electrons, and manufactured devices all have their backers. One of the key things that attracts backers is the tech's ability to scale. We'll need a lot of high-quality qubits to start doing any complex computations, and the ability of any technology to get us there is the subject of debate.

So even as some technologies can now support thousands of qubits, some competitors are still working on a small handful of qubits—the companies behind them are convinced that they have the potential to scale more effectively.

One of those technologies involves quantum dots that hold a single electron. Their advantage is that we can manufacture them using the same tech we use to build traditional processors, an approach that has proven to be scalable. This week saw two new papers describing different ways of using quantum dots, one of which was appealing enough that IBM bought the company that developed it. Separately, another company has released a processor showing 100 individual electrons being held in diamond defects, technology that wasn't obvious could scale.

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In a widely expected move, a committee organized by the Food and Drug Administration (FDA) has voted to endorse removing restrictions on the manufacture of peptides for human use. Thursday's panel meeting saw a sharply divided group recommend lifting limits on four peptides; votes on three additional peptides are scheduled for today. The move comes despite a continuing lack of evidence regarding their safety and effectiveness.

The move had been telegraphed months earlier as peptide enthusiast and Health and Human Services Secretary Robert F. Kennedy Jr. took steps to ensure this outcome.

Like proteins, peptides are composed of amino acids that are chemically linked into a chain. Peptides differ merely by length; they're often 10–20 amino acids long, in contrast to proteins, which can be hundreds or thousands. Some of them, such as insulin, are specifically made by targeted processing of a protein into shorter fragments, and the resulting peptide interacts with receptors that have evolved to send signals to cells based on its levels.

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A couple of decades after the discovery of systems that could selectively target DNA, we're starting to see the first therapies based on gene editing. One challenge these developments have faced is safety. While we can make them pretty specific to the gene we want edited, the human genome is very large, and even rare DNA sequences can appear a couple of times by chance.

As a result, all the original gene-editing systems had known rates of what are called off-target effects, in which they simply edit the wrong sequence. This may be a low-probability event, but edit enough cells—and therapies generally have to edit many—and errors become inevitable.

A lot of effort has gone into finding ways to minimize or eliminate off-target edits. In a recent issue of Nature, researchers described modifying the AI protein-folding software AlphaFold to help identify key areas of gene-editing proteins responsible for off-target effects. Those areas were then modified to reduce the problems.

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A couple of decades after the discovery of systems that could selectively target DNA, we're starting to see the first therapies based on gene editing. One challenge these developments have faced is safety. While we can make them pretty specific to the gene we want edited, the human genome is very large, and even rare DNA sequences can appear a couple of times by chance.

As a result, all the original gene-editing systems had known rates of what are called off-target effects, in which they simply edit the wrong sequence. This may be a low-probability event, but edit enough cells—and therapies generally have to edit many—and errors become inevitable.

A lot of effort has gone into finding ways to minimize or eliminate off-target edits. In a recent issue of Nature, researchers described modifying the AI protein-folding software AlphaFold to help identify key areas of gene-editing proteins responsible for off-target effects. Those areas were then modified to reduce the problems.

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On Tuesday, the White House Office of Science and Technology Policy (OSTP) released a report entitled "Science: A New Golden Age," in which it lays out how it has viewed science, found it lacking, and believes the Trump administration is in the perfect position to fix things. It's a bit unexpected coming from an administration that has been proposing crippling funding cuts to research and trying to enable political appointees to terminate grants awarded based on scientific merit.

The report presents itself as the spiritual successor of "Science, the Endless Frontier," a policy document that laid out the case for government-funded science in the wake of World War II. The New Golden Age (SNGA) says that, while the concepts promoted by the original remain vital, the circumstances have changed such that we need major revisions to how the government is implementing things.

The result is an odd mix. It completely ignores or glosses over many things that the administration is doing to harm scientific progress. In some cases, it identifies issues that have already been discussed as problems within the scientific community, but misrepresents them. Elsewhere, it's a mixture of political grievances, ideas without a solid intellectual foundation, and an injection of Silicon Valley's perspective on innovation (Michael Kratsios, the director of the OSTP, formerly worked with Peter Thiel). As a result, it's unlikely to have anything like the impact of "Science, the Endless Frontier."

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Climate change is being driven largely by the greenhouse gases we've pumped into the atmosphere, which trap more of the Sun's energy there. That added energy increases the odds of extreme events: longer, more intense heat waves and droughts, interspersed with excessive precipitation. But these sorts of events have happened in the past—how can we tell if any given weather disaster has been made more likely by the climate?

It's a question with implications for everything from building codes to disaster preparedness. And there's some good news: According to a report released by the US National Academies of Science on Thursday, the field of climate attribution is growing increasingly mature and can answer some questions for us with far greater confidence than it could just a decade ago. The report also notes that there are still important limits and suggests steps to address them.

Overall, this makes it clear that climate attribution is normal, mainstream science. And the fossil fuel industry views that as a problem, as it could make it easier to hold companies liable for damages. This has triggered a backlash that has Republicans in Congress and state governments threatening the National Academies' funding.

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Climate change is being driven largely by the greenhouse gases we've pumped into the atmosphere, which trap more of the Sun's energy there. That added energy increases the odds of extreme events: longer, more intense heat waves and droughts, interspersed with excessive precipitation. But these sorts of events have happened in the past—how can we tell if any given weather disaster has been made more likely by the climate?

It's a question with implications for everything from building codes to disaster preparedness. And there's some good news: According to a report released by the US National Academies of Science on Thursday, the field of climate attribution is growing increasingly mature and can answer some questions for us with far greater confidence than it could just a decade ago. The report also notes that there are still important limits and suggests steps to address them.

Overall, this makes it clear that climate attribution is normal, mainstream science. And the fossil fuel industry views that as a problem, as it could make it easier to hold companies liable for damages. This has triggered a backlash that has Republicans in Congress and state governments threatening the National Academies' funding.

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Most of the gas in the Universe is a mixture of hydrogen and helium. It's thought that the initial atmospheres of most planets also start out that way. However, over billions of years, as planets evolve, the composition of their atmospheres may shift. Hydrogen can react with other chemicals, and both it and helium can be lost to space. Venus, Earth, and Mars are thought to have second atmospheres, with their original hydrogen/helium envelopes having been lost and/or transformed.

The dynamics of loss are complicated. Lighter elements are lost more easily, but hydrogen can be protected by being incorporated into molecules like methane and ammonia. The gravity of the body can help retain some molecules, and a magnetic field can limit radiation's ability to blast material out of the atmosphere. Proximity to a star will matter too, both because of the radiation it produces and because it can heat the atmosphere and expand it to where gravity's influence is less substantial.

Given all these complications, it can be difficult to know what to expect to find on exoplanets. But a study in Wednesday's issue of Nature describes observations of helium being lost from the atmosphere of an exoplanet orbiting the star LHS 1140, about 50 light-years away. Based on the rate at which the helium is being lost, we can infer something about the remaining atmosphere.

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There are some obvious big picture issues that stand between us and useful quantum computing. Issues like whether we can make enough high-quality hardware qubits to connect into the error-corrected logical qubits we need, and how we generate the states needed to perform universal computation on those logical qubits. But there are also many less prominent challenges that will need to be solved before we can perform calculations.

One of those challenges, which only affects some types of hardware, is calibration. For devices we manufacture, like superconducting qubits, there are always subtle variations among individual qubits. (This is not true when we use something like an atom to hold the qubit, but the lasers that control them can drift.) As a result, this hardware is put through a process called calibration, where we test different frequencies and amplitudes of the microwave pulses that control them to find the combination that produces the lowest error rates, and then save those settings for use in calculations.

However, you can't perform the typical calibration process while you're doing calculations, which means drift becomes an issue for long and complicated algorithms. Google, though, has figured out that it's possible to do calibration using the same data that's used for error correction.

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One of the central features of plate tectonics is the formation of new crust at mid-ocean ridges. Part of the spreading process that drives continents apart, it was arguably the discovery of these ridges that drove widespread acceptance of plate tectonics as a theory. Thanks to decades of exploration, we now have a good picture of what the crust that forms at the site of spreading looks like. But we still have an incomplete idea of how its features are actually produced.

In other words, we have a good idea of the outcome of the process, but not a detailed picture of the process itself.

That is starting to change. In 2024, a team of French scientists was able to remotely monitor a major event on the border between the Australian and Antarctic plates, only two months after they installed equipment on the ocean floor. Their data shows that most of the spreading occurred in a relatively short time window, and some key events happened without any obvious seismic activity.

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Last week, just before the US started its break for the July Fourth holiday, the Nuclear Regulatory Commission (NRC) proposed a new rule that would change how it regulated exposure to radiation. The Trump administration has been pushing to restart construction of nuclear power plants in the US, and many pro-nuclear advocates have been complaining about the US's existing regulations, portraying them as the main barrier to the flourishing of the industry. So, it had seemed likely that major revisions were coming.

Instead, the NRC's proposed new rules endorse the science behind its current rules and suggest that any problems are largely in the vagueness of the terminology that it has been using. So, instead, it's endorsing standards that are meant to accomplish the same thing, but avoid using some of the language it had relied on. Probably the clearest indication of the evolutionary change at play is that the NRC estimates the changing rules will save industry—not just power, but also medical and research applications—only about $9.5 million a year.

LNT and ALARA

There are two technical abbreviations at the center of US nuclear regulations. The first is LNT, which stands for "linear non-threshold." It's in reference to the issue of whether there's any level of radiation that is so low that it no longer produces harmful biological effects—the "threshold" in LNT. The "non-threshold" implies that it doesn't, and that's in keeping with biology, which has demonstrated that even single particles or photons of radiation can damage DNA and that the mechanisms cells have for repairing that damage are inherently error-prone. The "linear" in LNT simply describes how the impact of radiation scales directly with the dose.

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Over decades, researchers in the US government and programs it sponsored built up a tremendous number of climate resources, from comprehensive analyses to massive datasets to basic explainers meant to inform the public. And people within the government built the climate.gov website to make it all accessible. But if you try to navigate there today, you get redirected to the climate page of the National Oceanic and Atmospheric Administration, and are greeted with the following message:

In compliance with Executive Order 14303 (“Restoring Gold Standard Science”), the White House Office of Science and Technology Policy’s June 23, 2025 Memorandum (“Agency Guidance for Implementing Gold Standard Science in the Conduct & Management of Scientific Activities”), 15 USC § 2904 (“National Climate Program”), 15 USC § 2934 (“National Global Change Research Plan”), and 33 USC § 893a (“NOAA Ocean and Atmospheric Science Education Programs”), you have been redirected to NOAA.gov. Future research products previously housed under Climate.gov will be available at NOAA.gov/climate and its affiliate websites.

Climate.gov was essentially gone, and the team that deleted implied that it happened because climate research somehow failed to uphold what the administration was calling "gold standard science."

But the people who put together climate.gov didn't go away. While the government didn't hesitate to delete inconvenient climate information, dedicated volunteers outside the government managed to preserve copies of much of the material, which the federal government is prohibited from copyrighting. The volunteers and former climate.gov admins got together and launched climate.us. On Tuesday, the team announced that it had completed the project to restore everything lost when climate.gov shut down.

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Over decades, researchers in the US government and programs it sponsored built up a tremendous number of climate resources, from comprehensive analyses to massive datasets to basic explainers meant to inform the public. And people within the government built the climate.gov website to make it all accessible. But if you try to navigate there today, you get redirected to the climate page of the National Oceanic and Atmospheric Administration, and are greeted with the following message:

In compliance with Executive Order 14303 (“Restoring Gold Standard Science”), the White House Office of Science and Technology Policy’s June 23, 2025 Memorandum (“Agency Guidance for Implementing Gold Standard Science in the Conduct & Management of Scientific Activities”), 15 USC § 2904 (“National Climate Program”), 15 USC § 2934 (“National Global Change Research Plan”), and 33 USC § 893a (“NOAA Ocean and Atmospheric Science Education Programs”), you have been redirected to NOAA.gov. Future research products previously housed under Climate.gov will be available at NOAA.gov/climate and its affiliate websites.

Climate.gov was essentially gone, and the team that deleted implied that it happened because climate research somehow failed to uphold what the administration was calling "gold standard science."

But the people who put together climate.gov didn't go away. While the government didn't hesitate to delete inconvenient climate information, dedicated volunteers outside the government managed to preserve copies of much of the material, which the federal government is prohibited from copyrighting. The volunteers and former climate.gov admins got together and launched climate.us. On Tuesday, the team announced that it had completed the project to restore everything lost when climate.gov shut down.

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